Triple
T30238395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marvell Wynne |
E768838
|
entity |
| Predicate | overallSelectionNumber |
P7664
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Marvell Wynne, overallSelectionNumber, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: overallSelectionNumber Context triple: [Marvell Wynne, overallSelectionNumber, 1]
-
A.
typicalNumberOfSelections
Indicates the usual or expected count of selections made in a given choice or selection process.
-
B.
typicalNumberOfSelectedFilms
Indicates the usual or average number of films that are chosen or selected in a given context or process.
-
C.
選出回数
Indicates the number of times an entity has been elected or selected to a position or role.
-
D.
selectedAt
Indicates that an entity was chosen or picked at a specific point in time or under particular selection conditions.
-
E.
hasTotalNumber
chosen
Indicates that an entity is associated with a specific overall count or sum of items, elements, or units.
- 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_69f224820c048190b1435c4cc145acf1 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6804d6ef081908267e0f6dc644557 |
completed | May 2, 2026, 10:53 p.m. |
| PD | Predicate disambiguation | batch_69f6760216108190bbb708d53a6c2c25 |
completed | May 2, 2026, 10:09 p.m. |
Created at: April 29, 2026, 7:38 p.m.