Triple
T14225023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Navi Mumbai |
E352594
|
entity |
| Predicate | hasCommercialHub |
P9422
|
FINISHED |
| Object | CBD Belapur |
E948626
|
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: CBD Belapur | Statement: [Navi Mumbai, hasCommercialHub, CBD Belapur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CBD Belapur Context triple: [Navi Mumbai, hasCommercialHub, CBD Belapur]
-
A.
Moolchand
Moolchand is a well-known locality and landmark area in South Delhi, India, recognized for its major hospital and its location along key city routes.
-
B.
Divya Pharmacy
Divya Pharmacy is an Indian Ayurvedic medicine and wellness products company closely associated with the Patanjali group and traditional yoga-based healthcare.
-
C.
Bapu Bazaar
Bapu Bazaar is a popular traditional market in Jaipur, India, known for its vibrant shops selling textiles, handicrafts, and local Rajasthani goods.
-
D.
Belapur
chosen
Belapur is a major suburban node in Navi Mumbai, India, known for its commercial centers, residential areas, and role as a key transport hub.
-
E.
Udyog Vihar
Udyog Vihar is a major industrial and commercial hub in Gurugram, Haryana, known for its concentration of corporate offices, manufacturing units, and business parks.
- 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_69d8278a06e481908b5d6af0a8afe737 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6228e53c8190abbe4e2d88a7362a |
completed | April 14, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd281611b48190b787e38ba9c733a4 |
completed | May 8, 2026, 12:02 a.m. |
Created at: April 10, 2026, 1:06 a.m.