Triple
T31022685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FIBA 3x3 Olympic tournament |
E790490
|
entity |
| Predicate | numberOfTeamsPerGenderAtTokyo2020 |
P6986
|
FINISHED |
| Object | 8 teams |
—
|
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: 8 teams | Statement: [FIBA 3x3 Olympic tournament, numberOfTeamsPerGenderAtTokyo2020, 8 teams]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTeamsPerGenderAtTokyo2020 Context triple: [FIBA 3x3 Olympic tournament, numberOfTeamsPerGenderAtTokyo2020, 8 teams]
-
A.
maximumTeamsPerNationPerGender
Indicates the upper limit on how many teams from a single nation are allowed to participate for each gender category.
-
B.
womenTeamsCount
Indicates the number of teams composed of women associated with a given entity or context.
-
C.
hasGenderedTeams
Indicates that the entity organizes or participates in teams that are separated or defined based on gender.
-
D.
hasGenderedTeam
Indicates that a team is organized or classified according to the gender of its members.
-
E.
hasNumberOfTeams
chosen
Indicates the quantity of teams associated with or contained by a given entity.
- 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_69f224c811508190a7de096a5b1f5798 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a00b8e0a5508190abc5c1e492bed12e |
completed | May 10, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_6a00b8327d048190850af317f60f0f8b |
completed | May 10, 2026, 4:54 p.m. |
Created at: April 29, 2026, 8:58 p.m.