Triple
T4664801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Onge |
E102818
|
entity |
| Predicate | autonym |
P1435
|
FINISHED |
| Object | Onge |
E18994
|
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: Onge | Statement: [Onge, autonym, Onge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Onge Context triple: [Onge, autonym, Onge]
-
A.
Onge
chosen
The Onge are one of the indigenous Negrito peoples of the Andaman Islands, known for their traditionally nomadic hunter-gatherer lifestyle and critically small population.
-
B.
Ongan
Ongan is a small language family comprising the indigenous Andamanese languages spoken primarily in the southern Andaman Islands of India.
-
C.
Ondenc
Ondenc is a rare, traditional white grape variety from southwest France, historically used in still and sweet wines and now cultivated in only a few appellations.
-
D.
Onne
Onne is a port town in Rivers State, Nigeria, known for its major oil and gas logistics base and deepwater port facilities.
-
E.
Ngundu
Ngundu is a small settlement in southern Zimbabwe that serves as a roadside stop and trading center along major routes between Harare and Beitbridge.
- 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_69bd43d9cba4819086c1ab1c2d9d2133 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd633aeba88190a8329ed022d685b6 |
completed | March 20, 2026, 3:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be03803a948190b6dc2a03bb9cdc93 |
completed | March 21, 2026, 2:33 a.m. |
Created at: March 20, 2026, 1:15 p.m.