Triple
T25844246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lewes F.C. |
E651018
|
entity |
| Predicate | womenTeamLeagueSystem |
P141828
|
FINISHED |
| Object | English women’s football league system |
—
|
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 women’s football league system | Statement: [Lewes F.C., womenTeamLeagueSystem, English women’s football league system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: womenTeamLeagueSystem Context triple: [Lewes F.C., womenTeamLeagueSystem, English women’s football league system]
-
A.
womenTeam
Indicates that the team is composed of women or is designated as a women’s team.
-
B.
hasWomenTeamInLeague
chosen
Indicates that an entity has a women’s team that participates in a specified league.
-
C.
featuresWomenTeams
Indicates that the subject includes, presents, or involves teams composed of women.
-
D.
womenTeamsCount
Indicates the number of teams composed of women associated with a given entity or context.
-
E.
womenTeamOrigin
Indicates that a women’s team originates from, is based in, or is otherwise associated with a particular place or organization.
- 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_69e7ab38086081908f3a8e7e0c6efd83 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f61f12b0f08190bc4a16907941864c |
completed | May 2, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69f61b37a5648190b10d33ae205ccfee |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 22, 2026, 7:51 a.m.