Triple
T22717146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FIFA 100 list |
E561764
|
entity |
| Predicate | numberOfFemalePlayers |
P7896
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [FIFA 100 list, numberOfFemalePlayers, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfFemalePlayers Context triple: [FIFA 100 list, numberOfFemalePlayers, 2]
-
A.
numberOfFemaleAthletes
chosen
Indicates the count of athletes who are female in a given context or group.
-
B.
minimumFemalePlayersOnField
Indicates the rule that specifies the least number of female players that must be present on the field at any given time.
-
C.
memberCountFemale
Indicates the number of female members associated with a given group or entity.
-
D.
eligiblePlayersGender
Indicates that the relationship specifies which player genders are allowed or considered eligible in a given context.
-
E.
hasFemaleCompetitors
Indicates that an entity participates in a competitive context where at least some of the competitors are female.
- 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_69e2454fc984819088213b58ee87a002 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1790e14c88190af6acb27910ae9c1 |
completed | April 29, 2026, 3:20 a.m. |
| PD | Predicate disambiguation | batch_69ee62bd657c81909f7b01245b080a5f |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:19 p.m.