Triple
T28905034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gold Clio |
E733048
|
entity |
| Predicate | categoryExamplesInclude |
P100896
|
FINISHED |
| Object | film |
—
|
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: film | Statement: [Gold Clio, categoryExamplesInclude, film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: categoryExamplesInclude Context triple: [Gold Clio, categoryExamplesInclude, film]
-
A.
categoryExample
Indicates that something is an example or instance illustrating a particular category.
-
B.
classificationIncludes
Indicates that a broader classification category encompasses or contains a specified subclass, member, or element within its scope.
-
C.
includesExamplesSuchAs
chosen
Indicates that one entity provides specific instances or samples that illustrate or clarify another entity.
-
D.
sampleCategory
Indicates that an item or instance belongs to, or is classified under, a particular sample category.
-
E.
categoryAbove
Indicates that one category is positioned higher than another in a hierarchy, ranking, or ordered structure.
- 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_69f05b096d208190958a57d2e4b5a93a |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f6691f5e188190b12c7b2eb729a45e |
completed | May 2, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69f6659b62fc8190b21555d0ba54db2d |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 8:06 a.m.