Triple
T7467679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dima Hasao district |
E176414
|
entity |
| Predicate | hasIndigenousCommunity |
P194
|
FINISHED |
| Object | Biate |
E637507
|
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: Biate | Statement: [Dima Hasao district, hasIndigenousCommunity, Biate]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Biate Context triple: [Dima Hasao district, hasIndigenousCommunity, Biate]
-
A.
Biate
chosen
Biate is a Tibeto-Burman language spoken by the Biate ethnic community in parts of northeast India, including areas of Cachar district in Assam.
-
B.
Bertogne
Bertogne is a rural municipality in the Luxembourg province of Wallonia in southeastern Belgium.
-
C.
Booué
Booué is a small town in central Gabon situated along the Ogooué River, known as a local transport and trading hub in the region.
-
D.
Biel
Biel is a surname most prominently associated with American actress and producer Jessica Biel.
-
E.
Begna
Begna is a river in southeastern Norway that flows through the region of Ringerike and is known for its role in local hydropower production and freshwater ecosystems.
- 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_69c69f223fd88190b4c69b95d7cbeeda |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f3f589cc81909f25268838c7c964 |
completed | March 27, 2026, 9:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c83475392c8190a51d24e1530c0c83 |
completed | March 28, 2026, 8:05 p.m. |
Created at: March 27, 2026, 3:40 p.m.