Triple
T14551032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stade de Genève |
E341416
|
entity |
| Predicate | hasPitchUse |
P38697
|
FINISHED |
| Object | professional 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: professional football | Statement: [Stade de Genève, hasPitchUse, professional football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPitchUse Context triple: [Stade de Genève, hasPitchUse, professional football]
-
A.
hasPitch
Indicates that one entity possesses or is characterized by a specific pitch (such as a tonal, acoustic, or frequency-related property).
-
B.
hasPitchLength
Indicates that an entity (such as a field or pitch) is associated with a specific measurement of its length.
-
C.
hasPitchType
chosen
Indicates that an entity is associated with, or characterized by, a specific type or category of pitch.
-
D.
usesInstrument
Indicates that an agent performs an action by employing a specific instrument or tool as the means to carry it out.
-
E.
hasHumanUse
Indicates that something is used, employed, or utilized by humans for a particular purpose or benefit.
- 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_69d822db9c8481908213ceb39585f792 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb2ee34208190bf040a513767c958 |
completed | April 14, 2026, 9:34 p.m. |
| PD | Predicate disambiguation | batch_69de5c546c7081909e27d504ec360c5c |
completed | April 14, 2026, 3:25 p.m. |
Created at: April 10, 2026, 1:23 a.m.