Triple
T11058595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guerrero metro station |
E261444
|
entity |
| Predicate | metroLine |
P848
|
FINISHED |
| Object |
Line 3
Line 3 is one of the main lines of the Mexico City Metro system, running in a generally north–south direction and serving several key neighborhoods and transfer stations.
|
E218789
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Line 3 | Statement: [Guerrero metro station, metroLine, Line 3]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 3 Context triple: [Guerrero metro station, metroLine, Line 3]
-
A.
Line 3
Line 3 is a route of Mexico City’s Metrobús bus rapid transit system that serves key corridors with dedicated lanes and high-capacity articulated buses.
-
B.
Line 3
Line 3 is a major north–south route of the Tehran Metro system, connecting key residential and commercial areas across the city.
-
C.
Line 3
Line 3 is a major north–south rapid transit route of the Shanghai Metro system, known for its elevated tracks and extensive coverage across the city.
-
D.
Line 3
Line 3 is a major line of the Moscow Metro system, known for serving central Moscow and connecting key residential and commercial districts.
-
E.
Line 3
Line 3 is one of the light rail routes of the Tunis Metro system, serving urban districts within the Tunis metropolitan area.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Line 3 Triple: [Guerrero metro station, metroLine, Line 3]
Generated description
Line 3 is one of the main lines of the Mexico City Metro system, running in a generally north–south direction and serving several key neighborhoods and transfer stations.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Line 3 Target entity description: Line 3 is one of the main lines of the Mexico City Metro system, running in a generally north–south direction and serving several key neighborhoods and transfer stations.
-
A.
Line 3
chosen
Line 3 is one of the main lines of the Mexico City Metro system, running in a generally north–south direction and serving several key residential and commercial areas.
-
B.
Line 3
Line 3 is a route of Mexico City’s Metrobús bus rapid transit system that serves key corridors with dedicated lanes and high-capacity articulated buses.
-
C.
Line 3
Line 3 is one of the main lines of the Paris Métro, running in an east–west direction across the city and serving several central districts.
-
D.
Line 3
Line 3 is one of the main lines of the Barcelona Metro system, running through central parts of the city and connecting several key stations and neighborhoods.
-
E.
Line 3
Line 3 is a rapid transit route of the Nanjing Metro system in Nanjing, China, serving as one of the city's main north–south subway lines.
- F. None of above.
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6aa98650481908609c7c56bfa7902 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d798a2efa48190b290f43dfe836501 |
completed | April 9, 2026, 12:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3c87ab0308190a6a6ada1708f0ec2 |
completed | April 18, 2026, 6:07 p.m. |
| NEDg | Description generation | batch_69e3cefc00148190a1850dc6e31523c3 |
completed | April 18, 2026, 6:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e3d014a644819092c76aa02b573ca9 |
completed | April 18, 2026, 6:40 p.m. |
Created at: April 8, 2026, 9:26 p.m.