Triple
T11821456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pat Jennings |
E281145
|
entity |
| Predicate | clubNumberOfAppearancesForArsenal |
P13108
|
FINISHED |
| Object | over 300 |
—
|
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: over 300 | Statement: [Pat Jennings, clubNumberOfAppearancesForArsenal, over 300]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: clubNumberOfAppearancesForArsenal Context triple: [Pat Jennings, clubNumberOfAppearancesForArsenal, over 300]
-
A.
clubAppearances
chosen
Indicates the number of official matches a player has played for a particular club.
-
B.
leagueAppearances
Indicates the number of times an entity has participated in official league matches or competitions.
-
C.
sportNumberOfAppearances
Indicates the total number of times an entity has participated in or appeared in a particular sport or sporting event.
-
D.
yearsAsPlayerAtClub
Indicates the number of years a person spent playing for a particular club.
-
E.
trophyWonWithArsenal
Indicates that a trophy was won by a person or team while they were with Arsenal Football Club.
- 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_69d6ab26aae88190b2489efcb2a24234 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a5e87e488190905bc3bb6d721e56 |
completed | April 10, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69d8a251fc08819095933f1d13c3b742 |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:42 p.m.