Triple
T2350803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Breakfast on Pluto |
E47442
|
entity |
| Predicate | protagonistGenderIdentity |
P38674
|
FINISHED |
| Object | transgender woman |
—
|
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: transgender woman | Statement: [Breakfast on Pluto, protagonistGenderIdentity, transgender woman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protagonistGenderIdentity Context triple: [Breakfast on Pluto, protagonistGenderIdentity, transgender woman]
-
A.
protagonistType
Indicates the role or category that the main character (protagonist) of a story or scenario belongs to.
-
B.
hasNeutralPronoun
Indicates that an entity is referred to using a gender-neutral pronoun.
-
C.
protagonistIs
Indicates that one entity serves as the main character or central figure in relation to another entity or narrative context.
-
D.
genderRule
Indicates a rule or constraint that determines how gender-related properties or classifications should be assigned or interpreted in a given context.
-
E.
protagonistEthnicity
Indicates the ethnic background or cultural heritage associated with a work’s main character.
- 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_69a88a1b678c8190bce986922ba60ce0 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abcb802da08190980100444010f91e |
completed | March 7, 2026, 6:53 a.m. |
| PD | Predicate disambiguation | batch_69abc5981ce48190a3f7852d28276e11 |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abcb7ebb708190ba7edffee3c45d8b |
completed | March 7, 2026, 6:53 a.m. |
Created at: March 4, 2026, 7:54 p.m.