Triple
T294034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Urdu |
E6054
|
entity |
| Predicate | officialLanguageOf |
P236
|
FINISHED |
| Object | West Bengal |
E31965
|
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: West Bengal | Statement: [Urdu, officialLanguageOf, West Bengal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: West Bengal Context triple: [Urdu, officialLanguageOf, West Bengal]
-
A.
West Bengal
chosen
West Bengal is an eastern Indian state known for its cultural heritage, literature, and the metropolis of Kolkata (formerly Calcutta).
-
B.
Bihar
Bihar is a populous state in eastern India known for its rich historical heritage, including ancient centers of learning like Nalanda and significant sites in Buddhist history.
-
C.
Assam
Assam is a northeastern region of the Indian subcontinent known for its tea plantations, rich biodiversity, and distinct cultural heritage.
-
D.
Tripura
Tripura is a small, hilly state in northeastern India known for its diverse tribal cultures, historical palaces, and dense forests.
-
E.
Uttar Pradesh
Uttar Pradesh is a populous northern Indian state known for its political influence, rich cultural and religious heritage, and historic cities such as Varanasi and Agra.
- 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_69a2e79114b081909490b3bf5a5dbb51 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2e978420881908488df342a7d5e90 |
completed | Feb. 28, 2026, 1:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a47d24fcd08190bdd981f0f2d50000 |
completed | March 1, 2026, 5:53 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.