Triple
T7784150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pink Line (Delhi Metro) |
E187198
|
entity |
| Predicate | lineNumber |
P1864
|
FINISHED |
| Object |
Line 7
Line 7 is the Pink Line of the Delhi Metro, a major orbital corridor that connects numerous key residential and commercial areas across Delhi.
|
E693489
|
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 7 | Statement: [Pink Line (Delhi Metro), lineNumber, Line 7]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 7 Context triple: [Pink Line (Delhi Metro), lineNumber, Line 7]
-
A.
Line 7
Line 7 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 7
Line 7 is one of the main lines of the Tehran Metro rapid transit network, serving various districts of Iran’s capital city.
-
C.
Line 7
Line 7 is a rapid transit route of the STC Metro system, serving as one of its numbered lines within the network.
-
D.
Line 7
Line 7 is a rapid transit line of the Guangzhou Metro system serving parts of Guangzhou and its surrounding areas.
-
E.
Line 7
Line 7 is a major rapid transit route of the Shanghai Metro that runs in a roughly north–south direction, connecting several key residential, commercial, and cultural areas across the city.
- 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 7 Triple: [Pink Line (Delhi Metro), lineNumber, Line 7]
Generated description
Line 7 is the Pink Line of the Delhi Metro, a major orbital corridor that connects numerous key residential and commercial areas across Delhi.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Line 7 Target entity description: Line 7 is the Pink Line of the Delhi Metro, a major orbital corridor that connects numerous key residential and commercial areas across Delhi.
-
A.
Line 7
Line 7 is a major rapid transit route of the Shanghai Metro that runs in a roughly north–south direction, connecting several key residential, commercial, and cultural areas across the city.
-
B.
Line 7
Line 7 is a major route of the Seoul Metropolitan Subway system that runs in a north–south diagonal across the city, connecting residential districts with key urban hubs.
-
C.
Line 7
Line 7 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving several key districts across the city.
-
D.
Line 7
Line 7 is an east–west rapid transit line of the Beijing Subway serving several central and southwestern districts of Beijing.
-
E.
Line 7
Line 7 is a rapid transit route of the STC Metro system, serving as one of its numbered lines within the network.
- F. None of above. chosen
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_69ca82af2d2c8190963861f5e0b8bf21 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cadf210f508190b215a0ab95192689 |
completed | March 30, 2026, 8:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69caf5f4fa6c8190a85ba9019c0e5345 |
completed | March 30, 2026, 10:15 p.m. |
| NEDg | Description generation | batch_69caf81ebde881909bd131da8987b449 |
completed | March 30, 2026, 10:24 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cafa013f348190a2067dee4a0c8c40 |
completed | March 30, 2026, 10:32 p.m. |
Created at: March 30, 2026, 4:22 p.m.