Triple
T33331181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry Bibby |
E853408
|
entity |
| Predicate | playedForUCLATitleTeams |
P185242
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Henry Bibby, playedForUCLATitleTeams, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: playedForUCLATitleTeams Context triple: [Henry Bibby, playedForUCLATitleTeams, yes]
-
A.
UEFAChampionsLeagueTitles
Indicates the number of UEFA Champions League titles an entity (typically a football club) has won.
-
B.
wonChampionsLeagueWith
Indicates that an entity achieved victory in the UEFA Champions League while being a member of or associated with a specified team or organization.
-
C.
UEFAEuropaLeagueTitles
Indicates the number of UEFA Europa League championship titles an entity has won.
-
D.
UEFAInterCitiesFairsCupTitles
Indicates the number of UEFA Inter-Cities Fairs Cup titles an entity has won.
-
E.
CAFChampionsLeagueTitle
Indicates that an entity has won the CAF Champions League title.
- 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_69f34969614c81909cd99661b0902533 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7bbf906d8819099020e548dd56bc9 |
completed | May 3, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a2dcf88190a7c9e109e41267be |
completed | May 3, 2026, 9:09 p.m. |
| PDg | Predicate description generation | batch_69f7bbf812cc8190a16917c5daaff2df |
completed | May 3, 2026, 9:19 p.m. |
Created at: May 1, 2026, 1:34 a.m.