Triple
T37980135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Basketball at the 2016 Summer Olympics |
E947528
|
entity |
| Predicate | numberOfMenTeams |
P204507
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [Basketball at the 2016 Summer Olympics, numberOfMenTeams, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMenTeams Context triple: [Basketball at the 2016 Summer Olympics, numberOfMenTeams, 12]
-
A.
hasNumberOfTeams
Indicates the quantity of teams associated with or contained by a given entity.
-
B.
womenTeamsCount
Indicates the number of teams composed of women associated with a given entity or context.
-
C.
hasMenTeam
Indicates that an entity possesses, is associated with, or fields a men’s team.
-
D.
qualifiedTeamsCount
Indicates the number of teams that have successfully met the criteria to qualify for a given stage, event, or competition.
-
E.
teamCountType
Indicates how the number of teams is categorized or measured within a given context.
- F. None of above. chosen
Provenance (4 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_69f76ef8a1d08190a741bbbc5970e3b3 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037cae084081909004d77514c5f286 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a192a008190a9917688a9e804f4 |
completed | May 12, 2026, 7:06 p.m. |
| PDg | Predicate description generation | batch_6a037c84ecbc81908232e5215355f43b |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:20 p.m.