Triple
T36396651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wimbledon gentlemen’s singles 1886 |
E896501
|
entity |
| Predicate | runnerUpSetsWonInFinal |
P185434
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Wimbledon gentlemen’s singles 1886, runnerUpSetsWonInFinal, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runnerUpSetsWonInFinal Context triple: [Wimbledon gentlemen’s singles 1886, runnerUpSetsWonInFinal, 1]
-
A.
runnerUpFinalFourCount
Indicates the number of times an entity has finished as the runner-up in a Final Four stage of a competition or tournament.
-
B.
runnerUpScore
Indicates the score achieved by the participant or entity that finished in second place in a competition or ranking.
-
C.
runnerUpFinalRecord
Indicates the final performance or outcome record associated with the entity that finished as runner-up in a competition or event.
-
D.
runnerUpWins
Indicates that an entity finishes in second place in a competition or ranking and receives the corresponding runner-up victory or award.
-
E.
gamesWonByRunnerUp
Indicates the number of games won by the runner-up in a competition or match.
- 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_69f76e52e3108190becf70b090ae7bd6 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bcccd7988190aa5c931ff347d33c |
completed | May 3, 2026, 9:23 p.m. |
| PDg | Predicate description generation | batch_69f7be9b9ab481908328e0e8d8ac73d4 |
completed | May 3, 2026, 9:31 p.m. |
Created at: May 3, 2026, 4:10 p.m.