Triple
T2583605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shango |
E57147
|
entity |
| Predicate | consort |
P13
|
FINISHED |
| Object | Oya |
E56231
|
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: Oya | Statement: [Shango, consort, Oya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oya Context triple: [Shango, consort, Oya]
-
A.
Oya
chosen
Oya is a powerful Yoruba orisha associated with storms, winds, transformation, and the Niger River.
-
B.
Yamate
Yamate is a historic hillside district in Yokohama known for its Western-style residences, foreign settlers’ heritage, and scenic views over the city and harbor.
-
C.
Moruya
Moruya is a coastal town in New South Wales, Australia, known for its scenic river setting, nearby beaches, and historic granite quarries.
-
D.
Kawaiisu
Kawaiisu is a Native American people and their Uto-Aztecan language traditionally spoken in the southern Sierra Nevada and Tehachapi Mountains of California.
-
E.
Oghi
Oghi is a town in Pakistan's Khyber Pakhtunkhwa province, known as a local administrative and commercial center within the Hazara region.
- 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_69ab4a4dca6481908c301f8e317396e7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3cb33a08190a3eae1a95e1b63bf |
completed | March 7, 2026, 7:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af83b4e09c8190909df4ba9b29d525 |
completed | March 10, 2026, 2:36 a.m. |
Created at: March 6, 2026, 9:49 p.m.