Triple
T14518070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bangalore Metro |
E340575
|
entity |
| Predicate | hasDepot |
P2413
|
FINISHED |
| Object | Peenya depot |
E340580
|
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: Peenya depot | Statement: [Bangalore Metro, hasDepot, Peenya depot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peenya depot Context triple: [Bangalore Metro, hasDepot, Peenya depot]
-
A.
Peenya depot
chosen
Peenya depot is a major maintenance and stabling facility serving Bengaluru’s Namma Metro system.
-
B.
Peenya industrial area
Peenya Industrial Area is one of the largest and oldest industrial hubs in Bengaluru, India, known for its dense concentration of manufacturing and small- to medium-scale industries.
-
C.
Kurla bus depot
Kurla bus depot is a major public bus terminal in the Kurla area of Mumbai, serving as an important hub for local and regional bus services.
-
D.
Byappanahalli depot
Byappanahalli depot is a major maintenance and stabling facility serving Bengaluru’s Namma Metro system, located near the Byappanahalli metro station.
-
E.
Koyambedu depot
Koyambedu depot is a major maintenance, operations, and stabling facility serving the Chennai Metro rail network in Chennai, India.
- 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_69d822d9c0408190b9a2b3643e58bb4d |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69de9a6f50208190b687b505f5cd1aa2 |
completed | April 14, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd6da80dc88190afa96760efb0c7de |
completed | May 8, 2026, 4:59 a.m. |
Created at: April 10, 2026, 1:22 a.m.