Triple
T16234468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 4 × 100 metres relay – Beijing 2015 |
E394067
|
entity |
| Predicate | numberOfRunnersPerTeam |
P89523
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [4 × 100 metres relay – Beijing 2015, numberOfRunnersPerTeam, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfRunnersPerTeam Context triple: [4 × 100 metres relay – Beijing 2015, numberOfRunnersPerTeam, 4]
-
A.
maximumScoringRunnersPerTeam
Indicates the maximum number of runners on a team who can be counted or considered based on their scoring performance.
-
B.
hasNumberOfTeams
Indicates the quantity of teams associated with or contained by a given entity.
-
C.
numberOfPlayersPerTeam
chosen
Indicates the quantity of players that are assigned to or allowed on each team in a given context.
-
D.
numberOfDriversPerTeam
Indicates the quantity of drivers associated with each team.
-
E.
numberOfTeamsVariesBetween
Indicates that the count of teams involved changes within a specified range or across different instances or conditions.
- 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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e23d2be2f881908ec2483507cb0b00 |
completed | April 17, 2026, 2:01 p.m. |
| PD | Predicate disambiguation | batch_69e219ee6f6481909663b388dc99770a |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:04 a.m.