Triple
T36245881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wimbledon gentlemen’s singles 1880 |
E891661
|
entity |
| Predicate | allComersRunnerUp |
P2683
|
FINISHED |
| Object | Otway Woodhouse |
—
|
NE NERFINISHED |
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: Otway Woodhouse | Statement: [Wimbledon gentlemen’s singles 1880, allComersRunnerUp, Otway Woodhouse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: allComersRunnerUp Context triple: [Wimbledon gentlemen’s singles 1880, allComersRunnerUp, Otway Woodhouse]
-
A.
runnerUp
chosen
Indicates that one entity finished in second place relative to another in a competition or ranking.
-
B.
conferenceOfRunnerUp
Indicates the conference or league affiliation to which the runner-up entity belongs.
-
C.
runnerUpWins
Indicates that an entity finishes in second place in a competition or ranking and receives the corresponding runner-up victory or award.
-
D.
runnerUpFullName
Indicates the full name of the entity that finished in second place in a competition or ranking.
-
E.
gamesWonByRunnerUp
Indicates the number of games won by the runner-up in a competition or match.
- 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_69f76e44993481908fa75e4c48d0aab3 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7ba6d06f48190a71b5a2f19e2232f |
completed | May 3, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a4aad48190a62e41c5e39339d9 |
completed | May 3, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:09 p.m.