Triple
T14664179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fantswam |
E344321
|
entity |
| Predicate | sharesCulturalAffinitiesWith |
P22474
|
FINISHED |
| Object | other Atyap subgroups |
—
|
LITERAL 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: other Atyap subgroups | Statement: [Fantswam, sharesCulturalAffinitiesWith, other Atyap subgroups]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sharesCulturalAffinitiesWith Context triple: [Fantswam, sharesCulturalAffinitiesWith, other Atyap subgroups]
-
A.
hasCulturalRelation
Indicates a relationship in which entities are connected through shared, influencing, or interacting cultural practices, values, traditions, or expressions.
-
B.
culturallySimilarTo
chosen
Indicates that two entities share comparable cultural characteristics, practices, or values.
-
C.
sharesCountryWith
Indicates that two entities are located in, originate from, or are otherwise associated with the same country.
-
D.
hasDistinctCultureFrom
Indicates that the culture of one entity is different and distinguishable from the culture of another entity.
-
E.
sharesLinguisticFamilyWith
Indicates that two languages belong to the same linguistic family or branch within a language family.
- F. None of above.
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_69d822e283fc8190a0e4c235cf880052 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb54ae5ac81908cc69891f280e5f7 |
completed | April 14, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_69de6576f0208190aa94d995e797ac38 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:27 a.m.