Triple
T3237587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | World Athletics Championships 2019 |
E67891
|
entity |
| Predicate | numberOfEventsWomen |
P2438
|
FINISHED |
| Object | 24 |
—
|
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: 24 | Statement: [World Athletics Championships 2019, numberOfEventsWomen, 24]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfEventsWomen Context triple: [World Athletics Championships 2019, numberOfEventsWomen, 24]
-
A.
numberOfEvents
chosen
Indicates the quantity or count of events associated with a given entity or context.
-
B.
numberOfFemaleAthletes
Indicates the count of athletes who are female in a given context or group.
-
C.
numberOfParticipants
Indicates the total count of entities involved in a particular event, activity, or relationship.
-
D.
hasWomenOrganization
Indicates that an entity is associated with, contains, or is part of an organization specifically for women.
-
E.
womenStatus
Indicates the social, legal, economic, or cultural position or condition assigned to women within a given context or system.
- 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_69ad858d27348190abb61c280b4c86a9 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaef29bf48190a9aa3a39f0138428 |
completed | March 8, 2026, 5:16 p.m. |
| PD | Predicate disambiguation | batch_69ada4159e0481908cbbdd750f5e08c7 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:08 p.m.