Triple
T23428367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Necho I |
E563254
|
entity |
| Predicate | opponent |
P437
|
FINISHED |
| Object | Tantamani |
—
|
NE NERFINISHED |
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: Tantamani | Statement: [Necho I, opponent, Tantamani]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tantamani Context triple: [Necho I, opponent, Tantamani]
-
A.
Tantamani
chosen
Tantamani was a Kushite king of the 25th Dynasty of Egypt, known for his brief attempt to restore Nubian control over Egypt before being driven back by the Assyrians.
-
B.
Tangale
Tangale is a West Chadic language spoken primarily in Gombe State, northeastern Nigeria, by the Tangale people.
-
C.
Tatanga
Tatanga is a recurring alien villain in the Super Mario series, best known as the main antagonist of Super Mario Land and nemesis of Princess Daisy.
-
D.
Nganzai
Nganzai is a local government area in Borno State, northeastern Nigeria, known for its rural communities and impact from the Boko Haram insurgency.
-
E.
Tamasopo
Tamasopo is a small town in the Huasteca Potosina region of San Luis Potosí, Mexico, known for its lush landscapes and popular nearby waterfalls and natural swimming areas.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24553980c8190bb66a2ae0bdab125 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1a54ba29881909945690496f28d65 |
completed | April 29, 2026, 6:29 a.m. |
Created at: April 17, 2026, 5:48 p.m.