Triple
T22103210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Filmfare Award for Best Comedian |
E546219
|
entity |
| Predicate | hasGenderSpecificity |
P119314
|
FINISHED |
| Object | primarily male recipients |
—
|
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: primarily male recipients | Statement: [Filmfare Award for Best Comedian, hasGenderSpecificity, primarily male recipients]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenderSpecificity Context triple: [Filmfare Award for Best Comedian, hasGenderSpecificity, primarily male recipients]
-
A.
genderSpecificity
chosen
Indicates whether the relationship or action applies specifically to a particular gender or is gender-neutral.
-
B.
hasGenderNeutrality
Indicates that something (such as a term, form, or expression) is neutral with respect to gender and does not specify or imply any particular gender.
-
C.
hasGenderDistinction
Indicates that a relationship, classification, or linguistic form differentiates entities based on gender categories.
-
D.
hasGenderFocus
Indicates that something is specifically concerned with, oriented toward, or primarily addressing a particular gender or gender-related issues.
-
E.
hasGenderVariant
Indicates that one entity is a gender-specific form or variant of another entity.
- 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_69e11e378dc08190896d6a51597afd5a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129175a7881909549883f23c53dca |
completed | April 28, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69e71b20ec50819096ac196c798f8e3c |
completed | April 21, 2026, 6:37 a.m. |
Created at: April 16, 2026, 8:30 p.m.