Triple
T31884822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nat Lofthouse |
E813979
|
entity |
| Predicate | appearancesForNationalTeam |
P13109
|
FINISHED |
| Object | 33 for England |
—
|
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: 33 for England | Statement: [Nat Lofthouse, appearancesForNationalTeam, 33 for England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appearancesForNationalTeam Context triple: [Nat Lofthouse, appearancesForNationalTeam, 33 for England]
-
A.
nationalTeamAppearances
chosen
Indicates the number of official matches in which an entity has represented its national team.
-
B.
hasPlayedForNationalTeam
Indicates that an athlete has been a member of and appeared in competition for a specified national team.
-
C.
playedForNationalTeamFrom
Indicates that an entity was a member of and played for a particular national team starting from a specified date or time period.
-
D.
representedNationalTeamInCompetition
Indicates that an individual was a member of and competed for a specific national team in a particular competition.
-
E.
playedForNationalTeamUntil
Indicates that an individual was a member of and actively played for a specified national team up to and including a particular end date or year.
- 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_69f348ed74bc81909846aaa6a3c7318c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fd2839880c819099a7a89783f2270e |
completed | May 8, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69fd23dc5da48190ae8ba08947d34956 |
completed | May 7, 2026, 11:44 p.m. |
Created at: April 30, 2026, 11:57 p.m.