Triple
T38262492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yomut Turkmens |
E1017963
|
entity |
| Predicate | historicalRivalryWith |
P22384
|
FINISHED |
| Object | Teke Turkmens |
E1038498
|
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: Teke Turkmens | Statement: [Yomut Turkmens, historicalRivalryWith, Teke Turkmens]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicalRivalryWith Context triple: [Yomut Turkmens, historicalRivalryWith, Teke Turkmens]
-
A.
hasHistoricRivalry
chosen
Indicates a long-standing, often competitive or adversarial relationship between two entities, typically rooted in significant past conflicts or repeated opposition.
-
B.
hasRivalryIn
Indicates that two entities are in a state of competition or opposition within a specific domain, context, or field.
-
C.
associatedRivalry
Indicates a relationship where one entity is linked to another as its rival, competitor, or opposing counterpart.
-
D.
hasNationalRivalry
Indicates that there is a notable, often historically rooted competitive or adversarial relationship between two nations.
-
E.
hasRivalryEmotion
Indicates that one entity feels rivalry-based emotions, such as competitive tension or antagonistic comparison, toward another entity.
- F. None of above.
Provenance (4 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_69f76de33e4481909099fa812709bd42 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a02206665508190ae2324d253ccf377 |
completed | May 11, 2026, 6:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a4193d4e2408190bd8893fc769eaaa2 |
completed | June 28, 2026, 9:36 p.m. |
| PD | Predicate disambiguation | batch_6a021fdc6e54819082847bedd97a680b |
completed | May 11, 2026, 6:28 p.m. |
Created at: May 3, 2026, 4:30 p.m.