Triple
T35104937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zambinella |
E1013125
|
entity |
| Predicate | genderIdentityTheme |
P182567
|
FINISHED |
| Object | ambiguous |
—
|
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: ambiguous | Statement: [Zambinella, genderIdentityTheme, ambiguous]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderIdentityTheme Context triple: [Zambinella, genderIdentityTheme, ambiguous]
-
A.
protagonistGenderIdentityTheme
Indicates that the work explores themes related to the protagonist’s gender identity and its development, expression, or impact within the narrative.
-
B.
hasGenderIdentity
Indicates that an entity identifies with or experiences a particular gender.
-
C.
genderVariation
Indicates that one entity is a variant or alternative form of another entity that differs specifically in grammatical or biological gender.
-
D.
genderVariant
Indicates that an entity’s gender identity or expression differs from traditional or expected norms associated with their assigned sex or gender.
-
E.
genderIdentityInSources
Indicates that the gender identity of an entity is recorded or referenced in one or more information sources.
- F. None of above. chosen
Provenance (4 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_69f76dd556248190808b4c4f43debebb |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7904a770481908ef3f788e51e8dba |
completed | May 3, 2026, 6:13 p.m. |
| PD | Predicate disambiguation | batch_69f78e2d71248190b850c2802ec170c0 |
completed | May 3, 2026, 6:04 p.m. |
| PDg | Predicate description generation | batch_69f78f629d508190b755848162c4e101 |
completed | May 3, 2026, 6:09 p.m. |
Created at: May 3, 2026, 4:01 p.m.