Triple
T36014665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ian Baker-Finch |
E1041804
|
entity |
| Predicate | yearOfBestResultInUSOpen |
P196341
|
FINISHED |
| Object | 1993 |
—
|
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: 1993 | Statement: [Ian Baker-Finch, yearOfBestResultInUSOpen, 1993]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearOfBestResultInUSOpen Context triple: [Ian Baker-Finch, yearOfBestResultInUSOpen, 1993]
-
A.
grandSlamBestResultUSOpen
Indicates the best performance or highest round an entity has achieved specifically at the US Open tennis Grand Slam tournament.
-
B.
numberOfUSOpenChampionshipsWon
Indicates the count of US Open Championship titles that an entity has won.
-
C.
yearOfBestResultInMastersTournament
Indicates the specific year in which an entity achieved its best performance or highest result in the Masters Tournament.
-
D.
wonUSOpen
Indicates that one entity achieved victory in the US Open competition or tournament over another entity or in a given year.
-
E.
hasBestGrandSlamResult
Indicates the relationship between an entity (e.g., a player) and the best performance or furthest round they have achieved in any Grand Slam tournament.
- 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_69f76e2b981881908e4e160607fa82eb |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fe21b0cba48190b56c39e9f1c0eafa |
completed | May 8, 2026, 5:47 p.m. |
| PD | Predicate disambiguation | batch_69fe204576848190aecf204e2adba5dc |
completed | May 8, 2026, 5:41 p.m. |
| PDg | Predicate description generation | batch_69fe21afdc4c8190913ac4b55a9a5f52 |
completed | May 8, 2026, 5:47 p.m. |
Created at: May 3, 2026, 4:07 p.m.