Triple
T3735131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lia Thomas |
E79162
|
entity |
| Predicate | transgenderIdentity |
P43613
|
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: [Lia Thomas, transgenderIdentity, transgender woman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transgenderIdentity Context triple: [Lia Thomas, transgenderIdentity, transgender woman]
-
A.
hasGenderIdentity
chosen
Indicates that an entity identifies with or experiences a particular gender.
-
B.
genderVariant
Indicates that an entity’s gender identity or expression differs from traditional or expected norms associated with their assigned sex or gender.
-
C.
genderReversalOf
Indicates that one entity is a counterpart of another with the same role or characteristics but with the opposite gender.
-
D.
protagonistGenderIdentity
Indicates the gender identity attributed to or expressed by the protagonist in a given context.
-
E.
sexOrGender
Indicates that one entity has a specified biological sex or socially constructed gender identity.
- 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_69ad8b0e4650819090ad7cef094285e8 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb39dc0881909cd74ff25d8c43a9 |
completed | March 8, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69adc04746588190b0dc535638f23546 |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:34 p.m.