Triple
T25040043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biarritz Olympique |
E627080
|
entity |
| Predicate | hasStrongHistoryIn |
P99136
|
FINISHED |
| Object | European competitions |
—
|
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: European competitions | Statement: [Biarritz Olympique, hasStrongHistoryIn, European competitions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStrongHistoryIn Context triple: [Biarritz Olympique, hasStrongHistoryIn, European competitions]
-
A.
hasHistoryIn
chosen
Indicates that an entity has a past involvement, presence, or record of activity within a particular domain, context, or location.
-
B.
hasLongHistory
Indicates that the relationship or subject has existed or persisted over a long period of time.
-
C.
hasPriorHistory
Indicates that an entity has a previously recorded occurrence, condition, or involvement relevant to the current context.
-
D.
hasHistoryOf
Indicates that an entity has a documented prior occurrence or background of a specified condition, event, or state.
-
E.
hasHistoricity
Indicates that something possesses historical existence, significance, or authenticity, rather than being purely fictional, mythical, or timeless.
- 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_69e2ff2a2c088190be513727ee8bfe78 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f62d89b89c8190afb372a8172111e7 |
completed | May 2, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69f62c1379f08190836c3e02b0c892df |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 18, 2026, 6:08 a.m.