Triple
T5635832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fataleka |
E147945
|
entity |
| Predicate | glottologName |
P6521
|
FINISHED |
| Object | Fataleka |
E147945
|
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: Fataleka | Statement: [Fataleka, glottologName, Fataleka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fataleka Context triple: [Fataleka, glottologName, Fataleka]
-
A.
Fataleka
chosen
Fataleka is an Oceanic language of the Southeast Solomonic group spoken by the Fataleka people in the Solomon Islands.
-
B.
Fatale
Fatale is a comic book series blending noir crime and supernatural horror, created by writer Ed Brubaker and artist Sean Phillips.
-
C.
Luvenda
Luvenda is an alternative name for Venda, a Bantu language and ethnic group primarily found in South Africa.
-
D.
Zabivaka
Zabivaka is the wolf character that served as the official mascot for major international football tournaments hosted by Russia, including the 2018 FIFA World Cup.
-
E.
Malumfashi
Malumfashi is a town and local government area in northern Nigeria known for its role as an administrative and commercial center within Katsina State.
- 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_69c00907bc8881909ed760d3ed73ef35 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0226286208190b6ccf036cc09fe82 |
completed | March 22, 2026, 5:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04d6d2dfc8190a2eabb8beda04ee5 |
completed | March 22, 2026, 8:13 p.m. |
Created at: March 22, 2026, 3:41 p.m.