Triple
T19816772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hvidovre |
E476077
|
entity |
| Predicate | hasSportsClub |
P346
|
FINISHED |
| Object | Hvidovre IF |
—
|
NE NERFINISHED |
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: Hvidovre IF | Statement: [Hvidovre, hasSportsClub, Hvidovre IF]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hvidovre IF Context triple: [Hvidovre, hasSportsClub, Hvidovre IF]
-
A.
Hvidovre IF
chosen
Hvidovre IF is a Danish football club known for developing notable players, including legendary goalkeeper Peter Schmeichel.
-
B.
Hvidovre IF youth
Hvidovre IF youth is the youth academy system of Danish football club Hvidovre IF, focused on developing young players for professional and senior-level competition.
-
C.
Vejle Boldklub
Vejle Boldklub is a Danish professional football club known for its historic success in the national league and cup competitions.
-
D.
Viborg FF
Viborg FF is a Danish professional football club based in Viborg that competes in the Danish Superliga.
-
E.
Haderslev FK
Haderslev FK is a Danish football club based in the town of Haderslev.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e654f9c5b08190987237f5144c3b37 |
completed | April 20, 2026, 4:31 p.m. |
Created at: April 10, 2026, 1:50 p.m.