Triple
T12162403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Gujarat |
E289740
|
entity |
| Predicate | majorCity |
P316
|
FINISHED |
| Object | Valsad |
E577543
|
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: Valsad | Statement: [South Gujarat, majorCity, Valsad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Valsad Context triple: [South Gujarat, majorCity, Valsad]
-
A.
Valsad
chosen
Valsad is a coastal city in southern Gujarat, India, known for its significant Parsi community, historical trading importance, and surrounding chikoo orchards.
-
B.
Powai
Powai is a prominent suburban neighborhood in Mumbai, India, known for Powai Lake, major residential and commercial developments, and the Indian Institute of Technology Bombay.
-
C.
Airoli
Airoli is a rapidly developing residential and commercial suburb in Navi Mumbai, Maharashtra, known for its IT parks and connectivity to Mumbai via the Thane–Belapur road and rail links.
-
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_69d6ab4d6c00819095a9a7c35de83cfb |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915c498a081908389598d0c247505 |
completed | April 10, 2026, 3:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f6a0baf0819094e90b7e92b979d4 |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 8, 2026, 9:50 p.m.