Triple
T1118417
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BAFTA Award for Best Supporting Actor |
E11153
|
entity |
| Predicate | hasWinnerGenderRestriction |
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: [BAFTA Award for Best Supporting Actor, hasWinnerGenderRestriction, male]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWinnerGenderRestriction Context triple: [BAFTA Award for Best Supporting Actor, hasWinnerGenderRestriction, male]
-
A.
hasGenderRequirement
Indicates that a particular role, activity, or context specifies a required or restricted gender for participation or eligibility.
-
B.
hasGenderPolicy
Indicates that an entity has adopted, implemented, or is governed by a specific policy related to gender issues or gender equality.
-
C.
hasPerformerGender
Indicates that an action, event, or performance is associated with the gender of the performer who carries it out.
-
D.
hasGenderSystem
Indicates that an entity employs or is characterized by a particular system for categorizing gender.
-
E.
awardCategoryGender
chosen
Indicates that an award category is designated for recipients of a specific gender.
- 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_69a493252a648190ac48f8742474a5e8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bc4bc21881909dcfe628f59f3e8c |
completed | March 1, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69a4bb4562f48190831e959f5f309956 |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:43 p.m.