Triple
T2486597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mumbai Suburban district |
E55940
|
entity |
| Predicate | contains |
P35
|
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: [Mumbai Suburban district, contains, Kurla]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kurla Context triple: [Mumbai Suburban district, contains, 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.
Dahisar
Dahisar is a suburban neighborhood in the northern part of Mumbai, India, known as one of the city's outermost residential areas.
-
E.
Andheri
Andheri is a major residential, commercial, and transport hub in Mumbai, India, known for its busy railway station, metro connectivity, and proximity to the city’s airports and film industry areas.
- 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_69ab49e670a88190b928e08302381710 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd17705488190b90b1aa66dd25972 |
completed | March 7, 2026, 7:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b12ded5f9c8190a0de21b631d970b0 |
completed | March 11, 2026, 8:55 a.m. |
Created at: March 6, 2026, 9:45 p.m.