Triple
T28266170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Romanian football league system |
E712708
|
entity |
| Predicate | hasWomenCompetitions |
P80775
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Romanian football league system, hasWomenCompetitions, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWomenCompetitions Context triple: [Romanian football league system, hasWomenCompetitions, true]
-
A.
hasFemaleCompetitors
Indicates that an entity participates in a competitive context where at least some of the competitors are female.
-
B.
hasWomenSeries
Indicates that an entity is associated with or includes a series specifically for women.
-
C.
hasWomenTeamInLeague
Indicates that an entity has a women’s team that participates in a specified league.
-
D.
hasMaleAthletes
Indicates that an entity is associated with or includes one or more male athletes.
-
E.
includesWomen'sLeagues
chosen
Indicates that the subject entity encompasses, offers, or is associated with one or more leagues specifically organized for women.
- 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_69efb5216c6881908020dce4aea65381 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f7886be6d8819095ec62e4f2cee858 |
completed | May 3, 2026, 5:39 p.m. |
| PD | Predicate disambiguation | batch_69f7841440f48190b4346c08855951d2 |
completed | May 3, 2026, 5:21 p.m. |
Created at: April 27, 2026, 11:14 p.m.