Triple
T16656558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VII Olympic Winter Games |
E404745
|
entity |
| Predicate | disciplineCount |
P124155
|
FINISHED |
| Object | 8 |
—
|
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: 8 | Statement: [VII Olympic Winter Games, disciplineCount, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: disciplineCount Context triple: [VII Olympic Winter Games, disciplineCount, 8]
-
A.
subjectCount
Indicates the number of subjects associated with or involved in a given entity or context.
-
B.
numberOfQualifiersPerDiscipline
Indicates the count of qualifier instances associated with each specific discipline.
-
C.
typeDiscipline
Indicates that an entity is associated with, categorized under, or characterized by a particular discipline or field of study.
-
D.
disciplineCode
Indicates the specific field, subject area, or branch of study/classification to which an entity is assigned or categorized.
-
E.
disciplineFormat
Indicates the specific organizational or presentation format in which a discipline or field of study is structured or expressed.
- F. None of above. chosen
Provenance (4 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_69d8838b5fbc81908c6575c132b82e80 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37bfb2b308190bf3559df9fbb126f |
completed | April 18, 2026, 12:41 p.m. |
| PD | Predicate disambiguation | batch_69e319b1d7f08190b5ecb4a68c636c15 |
completed | April 18, 2026, 5:42 a.m. |
| PDg | Predicate description generation | batch_69e326b9e84881909a9166e65bd850d6 |
completed | April 18, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:18 a.m.