Triple
T34637765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wimbledon gentlemen’s singles title 1887 |
E889475
|
entity |
| Predicate | nationalityOfChampion |
P104081
|
FINISHED |
| Object | British |
—
|
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: British | Statement: [Wimbledon gentlemen’s singles title 1887, nationalityOfChampion, British]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalityOfChampion Context triple: [Wimbledon gentlemen’s singles title 1887, nationalityOfChampion, British]
-
A.
nationalityOfWinner
Indicates the country or nationality associated with the winner of a given event or competition.
-
B.
championNationality
chosen
Indicates the country or nationality that a champion represents or is associated with.
-
C.
heroNationality
Indicates the country or national identity associated with a hero.
-
D.
memberNationality
Indicates that an entity is the country or nationality associated with a particular member or individual.
-
E.
winnerCountry
Indicates the country that achieved first place or victory in a given competition, event, or contest.
- 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_69f349d724848190b63ad3407e0006d9 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fd68abf52881909c5a390c362b7c59 |
completed | May 8, 2026, 4:38 a.m. |
| PD | Predicate disambiguation | batch_69fd6812d0c88190930d8fa2d4b92490 |
completed | May 8, 2026, 4:35 a.m. |
Created at: May 1, 2026, 2:04 a.m.