Triple
T21631684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olympic curling tournaments |
E533844
|
entity |
| Predicate | numberOfPlayersPerTeamInMenAndWomenEvents |
P89523
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Olympic curling tournaments, numberOfPlayersPerTeamInMenAndWomenEvents, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPlayersPerTeamInMenAndWomenEvents Context triple: [Olympic curling tournaments, numberOfPlayersPerTeamInMenAndWomenEvents, 4]
-
A.
numberOfPlayersPerTeam
chosen
Indicates the quantity of players that are assigned to or allowed on each team in a given context.
-
B.
maximumTeamsPerNationPerGender
Indicates the upper limit on how many teams from a single nation are allowed to participate for each gender category.
-
C.
playersPerMatch
Indicates the number of players that participate in a single match.
-
D.
usesNumberOfPlayersOnFieldPerTeam
Indicates that the relationship specifies or depends on how many players each team has on the field at a given time.
-
E.
minimumFemalePlayersOnField
Indicates the rule that specifies the least number of female players that must be present on the field at any given time.
- 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_69e0c465ae7481908577b7209fdb2a77 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef5217952c8190910c2103fb4a27d9 |
completed | April 27, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69e69677b9c48190bf81f795aa8ad74e |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:34 p.m.