Triple
T1142140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Football Writers' Association Footballer of the Year |
E23475
|
entity |
| Predicate | leagueScope |
P3228
|
FINISHED |
| Object | English football |
—
|
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: English football | Statement: [Football Writers' Association Footballer of the Year, leagueScope, English football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leagueScope Context triple: [Football Writers' Association Footballer of the Year, leagueScope, English football]
-
A.
leagueContext
chosen
Indicates the broader league or competition setting within which the relationship or action takes place.
-
B.
league
Indicates that an organization or team participates in, is a member of, or is associated with a particular sports or competitive league.
-
C.
league2
Indicates that an entity participates in, is a member of, or is otherwise affiliated with a specific sports league or competitive organization.
-
D.
leagueType
Indicates the classification or category of a league within a broader organizational or competitive structure.
-
E.
leagueDepicted
Indicates that a work or representation visually portrays or features a particular sports league.
- 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_69a493ef399c8190b04b9146d2314f59 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bc4d414881908fc636e8ccbc4c34 |
completed | March 1, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69a4bb4d4104819084027a043c6118cb |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:44 p.m.