Triple
T2015474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dominique Gisin |
E43784
|
entity |
| Predicate | disciplineSpecialization |
P592
|
FINISHED |
| Object | downhill |
—
|
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: downhill | Statement: [Dominique Gisin, disciplineSpecialization, downhill]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: disciplineSpecialization Context triple: [Dominique Gisin, disciplineSpecialization, downhill]
-
A.
subDisciplineOf
Indicates that one discipline is a more specialized or narrower field within another, broader discipline.
-
B.
associatedWithDiscipline
chosen
Indicates that an entity has a relevant connection or involvement with a particular academic, professional, or thematic discipline.
-
C.
featuredDiscipline
Indicates that one discipline is highlighted or given special prominence in relation to another entity or context.
-
D.
typeDiscipline
Indicates that an entity is associated with, categorized under, or characterized by a particular discipline or field of study.
-
E.
hasSubdiscipline
Indicates that one discipline includes another, more specialized field of study as a subordinate branch.
- 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_69a88716e9f08190946313fdc949e3cf |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb8cb16048190bc626685fbb5f707 |
completed | March 7, 2026, 5:34 a.m. |
| PD | Predicate disambiguation | batch_69abb7a03a1c81909ad50d56667db2d5 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:37 p.m.