Triple
T2460174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mumbai Suburban Railway |
E54514
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object | Thane |
E168787
|
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: Thane | Statement: [Mumbai Suburban Railway, hasStation, Thane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thane Context triple: [Mumbai Suburban Railway, hasStation, Thane]
-
A.
Thane
chosen
Thane is a major city in western India known for its numerous lakes and its proximity to Mumbai.
-
B.
Kurla
Kurla is a densely populated suburban neighborhood in Mumbai, India, known as a major residential, commercial, and transport hub of the city.
-
C.
Vadodara
Vadodara is a major city in western India known for its rich cultural heritage, educational institutions, and industrial development.
-
D.
Dadar
Dadar is a major commercial and residential neighborhood in central Mumbai, India, known as a key transit hub and marketplace in the city.
-
E.
Pune
Pune is a major cultural, educational, and IT hub in the western Indian state of Maharashtra, known for its universities, historical significance, and rapidly growing urban economy.
- 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_69ab49dee84c819096b50a0049c347ac |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd10ba66481909580e994b22fd406 |
completed | March 7, 2026, 7:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af98a63a44819092c017b8624e3dc8 |
completed | March 10, 2026, 4:05 a.m. |
Created at: March 6, 2026, 9:44 p.m.