Triple
T7252555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fataleka language |
E157637
|
entity |
| Predicate | hasGlottologName |
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 language, hasGlottologName, Fataleka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fataleka Context triple: [Fataleka language, hasGlottologName, 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.
Shikasta
Shikasta is a 1979 science fiction novel by Doris Lessing that inaugurates her Canopus in Argos series, blending cosmic history with political and spiritual allegory.
-
E.
Neszmély
Neszmély is a village in northwestern Hungary on the Danube River, historically noted as the place where Holy Roman Emperor Albert II died.
- 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_69c6882d81d4819085f7ff862951ee4f |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea7ae0e48190bd80c91bad1976c6 |
completed | March 27, 2026, 8:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7d3ac0de88190990c1ef25636260c |
completed | March 28, 2026, 1:12 p.m. |
Created at: March 27, 2026, 2:56 p.m.