Triple
T35538924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Howard Webb |
E1027006
|
entity |
| Predicate | yearOfNotableDoubleFinals |
P196060
|
FINISHED |
| Object | 2010 |
—
|
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: 2010 | Statement: [Howard Webb, yearOfNotableDoubleFinals, 2010]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearOfNotableDoubleFinals Context triple: [Howard Webb, yearOfNotableDoubleFinals, 2010]
-
A.
numberOfGamesInFinals
Indicates the total count of games played in the finals stage of a competition or series.
-
B.
hasDoublesChampionEachYear
Indicates that for each year in consideration, there exists at least one recognized doubles champion associated with that year.
-
C.
playedInFinals
Indicates that an entity participated as a competitor or player in the final round of a competition or tournament.
-
D.
firstYearWithTwoLeagueWinners
Indicates the first year in which two different teams or competitors both won league titles.
-
E.
hasFinalsSeries
Indicates that there exists a specific finals series associated with or assigned to a given entity.
- 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_69f76e008ba08190927acd8e5e0344c8 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fe031bc6208190860099aef72d8dcb |
completed | May 8, 2026, 3:36 p.m. |
| PD | Predicate disambiguation | batch_69fe014c8b388190b5d4e0cb95ee2be5 |
completed | May 8, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69fe031af3248190816da6829aef7bab |
completed | May 8, 2026, 3:36 p.m. |
Created at: May 3, 2026, 4:04 p.m.