Triple
T28180057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Actor for The Front Page |
E716001
|
entity |
| Predicate | awardGenderCategory |
P23180
|
FINISHED |
| Object | male |
—
|
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: male | Statement: [Academy Award for Best Actor for The Front Page, awardGenderCategory, male]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: awardGenderCategory Context triple: [Academy Award for Best Actor for The Front Page, awardGenderCategory, male]
-
A.
awardCategoryGender
chosen
Indicates that an award category is designated for recipients of a specific gender.
-
B.
awardType
Indicates the specific category or kind of award associated with an entity or event.
-
C.
notableAwardCategory
Indicates that an award is recognized as a significant or distinguished category within a broader system of awards.
-
D.
awardName
Indicates the specific name or title of an award associated with an entity.
-
E.
awardNameIncludes
Indicates that the name of an award contains the specified text or substring.
- 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_69efd6b4fc5c81909dd88f01a8c2b35d |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f71996e1a48190ac59a1d66d7c44e8 |
completed | May 3, 2026, 9:47 a.m. |
| PD | Predicate disambiguation | batch_69f71820c6c88190ab38b4fa626d22cc |
completed | May 3, 2026, 9:40 a.m. |
Created at: April 27, 2026, 10:19 p.m.