Triple
T16132005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kurla railway station |
E391420
|
entity |
| Predicate | suburbServed |
P46405
|
FINISHED |
| Object | Kurla |
E274832
|
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: Kurla | Statement: [Kurla railway station, suburbServed, Kurla]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kurla Context triple: [Kurla railway station, suburbServed, Kurla]
-
A.
Kurla
chosen
Kurla is a densely populated suburban neighborhood in Mumbai, India, known as a major residential, commercial, and transport hub of the city.
-
B.
Dadar
Dadar is a major commercial and residential neighborhood in central Mumbai, India, known as a key transit hub and marketplace in the city.
-
C.
Thane
Thane is a major city in western India known for its numerous lakes and its proximity to Mumbai.
-
D.
Mumbra
Mumbra is a densely populated suburban area in the Thane district of Maharashtra, India, known for its largely Muslim population and rapid urban growth.
-
E.
Kopar Khairane
Kopar Khairane is a rapidly developing residential and commercial node in Navi Mumbai, Maharashtra, known for its growing infrastructure and connectivity to Mumbai and Thane.
- 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21a02172c8190978f7951ccd80928 |
completed | April 17, 2026, 11:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff7a0ed9c8190a10fa88ee94811cb |
completed | May 10, 2026, 3:12 a.m. |
Created at: April 10, 2026, 5:01 a.m.