Triple
T29133215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tim Henman |
E738435
|
entity |
| Predicate | roleInBritishTennis |
P198185
|
FINISHED |
| Object | revitalized British tennis in the 1990s and early 2000s |
—
|
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: revitalized British tennis in the 1990s and early 2000s | Statement: [Tim Henman, roleInBritishTennis, revitalized British tennis in the 1990s and early 2000s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInBritishTennis Context triple: [Tim Henman, roleInBritishTennis, revitalized British tennis in the 1990s and early 2000s]
-
A.
roleInTennis
Indicates the specific function or position an entity holds within the context of tennis (e.g., player, coach, umpire).
-
B.
roleAtWilliams
Indicates that an entity holds or has held a specific role or position at Williams (e.g., Williams College or a Williams-affiliated organization).
-
C.
RyderCupRole
Indicates that an entity holds a specific role or position in relation to the Ryder Cup event.
-
D.
roleInTigerWoodsCareer
Indicates the specific function, position, or contribution an entity has had within the context of Tiger Woods’s professional golf career.
-
E.
formerWorldNo1
Indicates that the subject was ranked number one in the world in the past, but does not hold that top ranking currently.
- 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_69f07cb3adb48190a9e0e169cd026634 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69fed09a12648190affcd9bacf7ca275 |
completed | May 9, 2026, 6:13 a.m. |
| PD | Predicate disambiguation | batch_69fecf91d6f481908deb60c965c433ed |
completed | May 9, 2026, 6:09 a.m. |
| PDg | Predicate description generation | batch_69fed098328c819085979de6b179b378 |
completed | May 9, 2026, 6:13 a.m. |
Created at: April 28, 2026, 11:33 a.m.