Triple
T18061128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beijing 2008 Olympic beach volleyball tournament |
E432174
|
entity |
| Predicate | maximumTeamsPerNationPerGender |
P129670
|
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: [Beijing 2008 Olympic beach volleyball tournament, maximumTeamsPerNationPerGender, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumTeamsPerNationPerGender Context triple: [Beijing 2008 Olympic beach volleyball tournament, maximumTeamsPerNationPerGender, 2]
-
A.
maximumAthletesPerNOC
Indicates the maximum number of athletes that any single National Olympic Committee (NOC) is allowed to enter or have participate in a given event or competition.
-
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.
numberOfPlayersPerTeam
Indicates the quantity of players that are assigned to or allowed on each team in a given context.
-
E.
maximumScholarshipsPerTeam
Indicates the highest number of scholarships that any single team is allowed to award or hold.
- 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_69d8b9070cac81909fa9473fb1c3f1c7 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4c1066f508190bacf1122e366f87b |
completed | April 19, 2026, 11:48 a.m. |
| PD | Predicate disambiguation | batch_69e3f90c652481908133a73106d78919 |
completed | April 18, 2026, 9:35 p.m. |
| PDg | Predicate description generation | batch_69e42d8eefa88190a700c7c1b4213e46 |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 10, 2026, 10:26 a.m.