Triple
T13815048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | short track speed skating at the 1992 Winter Olympics |
E331991
|
entity |
| Predicate | womenCompetitors |
P7896
|
FINISHED |
| Object | 42 |
—
|
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: 42 | Statement: [short track speed skating at the 1992 Winter Olympics, womenCompetitors, 42]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: womenCompetitors Context triple: [short track speed skating at the 1992 Winter Olympics, womenCompetitors, 42]
-
A.
womenMainEventParticipants
Indicates that the referenced entities are participants in a main event specifically designated for women.
-
B.
numberOfFemaleAthletes
chosen
Indicates the count of athletes who are female in a given context or group.
-
C.
womenTeam
Indicates that the team is composed of women or is designated as a women’s team.
-
D.
womenStatus
Indicates the social, legal, economic, or cultural position or condition assigned to women within a given context or system.
-
E.
femaleMass
Indicates that the subject has a mass value specifically associated with its female form or female population.
- 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_69d81c59f8808190a851bc56afdc55e9 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02806e148190996f58934e66d7d8 |
completed | April 14, 2026, 9:01 a.m. |
| PD | Predicate disambiguation | batch_69dbc862e9608190bd8a3d883959b7e4 |
completed | April 12, 2026, 4:29 p.m. |
Created at: April 9, 2026, 10:12 p.m.