Triple
T21527210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shivaji Park, Dadar, Mumbai |
E531126
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Dadar |
—
|
NE NERFINISHED |
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: Dadar | Statement: [Shivaji Park, Dadar, Mumbai, locatedIn, Dadar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dadar Context triple: [Shivaji Park, Dadar, Mumbai, locatedIn, Dadar]
-
A.
Dadar
chosen
Dadar is a major commercial and residential neighborhood in central Mumbai, India, known as a key transit hub and marketplace in the city.
-
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.
Vasai-Virar
Vasai-Virar is a rapidly growing suburban city and municipal corporation in the northern part of the Mumbai metropolitan area in Maharashtra, India.
-
D.
Thane
Thane is a major city in western India known for its numerous lakes and its proximity to Mumbai.
-
E.
Seemapuri
Seemapuri is a densely populated, low-income residential area on the northeastern edge of Delhi, India, known for its informal settlements and migrant communities.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c45e5b8881908ac18fc2f493b114 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee88522e948190b9fa5a3587f32eae |
completed | April 26, 2026, 9:49 p.m. |
Created at: April 16, 2026, 6:26 p.m.