Triple
T33700456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Recruiting Officer |
E863440
|
entity |
| Predicate | hasFemaleCharacterInMaleDisguise |
P146968
|
FINISHED |
| Object | Sylvia |
—
|
NE NERFINISHED |
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: Sylvia | Statement: [The Recruiting Officer, hasFemaleCharacterInMaleDisguise, Sylvia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFemaleCharacterInMaleDisguise Context triple: [The Recruiting Officer, hasFemaleCharacterInMaleDisguise, Sylvia]
-
A.
hasCrossDressingProtagonist
chosen
Indicates that the main character in the work regularly dresses in clothing traditionally associated with another gender.
-
B.
hasFemaleCharacter
Indicates that an entity includes or features at least one female character.
-
C.
hasFemaleEquivalent
Indicates that one entity serves as the female counterpart or equivalent of another entity.
-
D.
hasLeadCharacterGender
Indicates that the primary or lead character in a work has a specified gender.
-
E.
isMaleCharacter
Indicates that the referenced character is identified as male.
- 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_69f3498723a08190ac034339cc78eade |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7b5ccbda481908fe1945c35e36ce8 |
completed | May 3, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c06f5881908f0b98cad6796478 |
completed | May 3, 2026, 8:49 p.m. |
Created at: May 1, 2026, 1:43 a.m.