Triple
T1959875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indios Verdes |
E42358
|
entity |
| Predicate | partOfLine |
P6309
|
FINISHED |
| Object | Line 3 |
E43034
|
NE FINISHED |
How this triple was built (2 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: [Indios Verdes, partOfLine, Line 3]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 3 Context triple: [Indios Verdes, partOfLine, Line 3]
-
A.
Line 3
chosen
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 rapid transit route of the Guangzhou Metro system, known for its high passenger volume and key role in connecting central urban areas with the airport and suburban districts.
-
C.
Line 3
Line 3 is a major north–south route of the Tehran Metro system, connecting key residential and commercial areas across the city.
-
D.
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.
-
E.
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 residential and commercial areas.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a8870eea088190a38781990812a9bc |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb37f737881908130bb828affcaa2 |
completed | March 7, 2026, 5:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae031ef4e48190af93dfd6f33184d3 |
completed | March 8, 2026, 11:15 p.m. |
Created at: March 4, 2026, 7:36 p.m.