Triple
T3258291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chennai Metro |
E68347
|
entity |
| Predicate | hasDepot |
P2413
|
FINISHED |
| Object |
Wimco Nagar depot
Wimco Nagar depot is a maintenance and stabling facility serving the northern stretch of the Chennai Metro network in Chennai, India.
|
E343312
|
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: Wimco Nagar depot | Statement: [Chennai Metro, hasDepot, Wimco Nagar depot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wimco Nagar depot Context triple: [Chennai Metro, hasDepot, Wimco Nagar depot]
-
A.
Byappanahalli depot
Byappanahalli depot is a major maintenance and stabling facility serving Bengaluru’s Namma Metro system, located near the Byappanahalli metro station.
-
B.
Peenya depot
Peenya depot is a major maintenance and stabling facility serving Bengaluru’s Namma Metro system.
-
C.
Wadala Depot
Wadala Depot is a key station and maintenance hub on the Mumbai Monorail network, serving the Wadala area of Mumbai, India.
-
D.
Sibi Railway Station
Sibi Railway Station is a key railway junction in Balochistan, Pakistan, serving as an important stop on major national rail routes.
-
E.
Pontinha depot
Pontinha depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
- 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: Wimco Nagar depot Triple: [Chennai Metro, hasDepot, Wimco Nagar depot]
Generated description
Wimco Nagar depot is a maintenance and stabling facility serving the northern stretch of the Chennai Metro network in Chennai, India.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wimco Nagar depot Target entity description: Wimco Nagar depot is a maintenance and stabling facility serving the northern stretch of the Chennai Metro network in Chennai, India.
-
A.
Byappanahalli depot
Byappanahalli depot is a major maintenance and stabling facility serving Bengaluru’s Namma Metro system, located near the Byappanahalli metro station.
-
B.
Peenya depot
Peenya depot is a major maintenance and stabling facility serving Bengaluru’s Namma Metro system.
-
C.
Wadala Depot
Wadala Depot is a key station and maintenance hub on the Mumbai Monorail network, serving the Wadala area of Mumbai, India.
-
D.
Sibi Railway Station
Sibi Railway Station is a key railway junction in Balochistan, Pakistan, serving as an important stop on major national rail routes.
-
E.
Pontinha depot
Pontinha depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
- 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_69ad858f74408190bcbd07f967cd7bd0 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaf6a46448190a7fa0ca83fa096f8 |
completed | March 8, 2026, 5:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b28ed3a7908190bfab434a64af5f2f |
completed | March 12, 2026, 10 a.m. |
| NEDg | Description generation | batch_69b2903dd0ac819088499f06edfeac56 |
completed | March 12, 2026, 10:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b2d6bf36988190b394766e9821047c |
completed | March 12, 2026, 3:07 p.m. |
Created at: March 8, 2026, 3:09 p.m.