Triple
T28899389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poison |
E732911
|
entity |
| Predicate | genderIdentityInJapaneseMaterials |
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: [Poison, genderIdentityInJapaneseMaterials, transgender woman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderIdentityInJapaneseMaterials Context triple: [Poison, genderIdentityInJapaneseMaterials, transgender woman]
-
A.
nameGenderInJapaneseContext
Indicates that a given name is associated with a particular gender within Japanese cultural and linguistic conventions.
-
B.
genderIdentityInSources
Indicates that the gender identity of an entity is recorded or referenced in one or more information sources.
-
C.
hasGenderIdentity
chosen
Indicates that an entity identifies with or experiences a particular gender.
-
D.
exploresGenderIdentity
Indicates engaging in a process of examining, questioning, or discovering one’s own gender identity.
-
E.
publiclyIdentifiesAs
Indicates that an entity openly declares or presents themself to others as having a particular identity or role.
- 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_69f05b08c2008190ac426a035a2ed66d |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f65aa677948190ab5b5a097d4cea5d |
completed | May 2, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f6576487e081908d802f1caf59c423 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 28, 2026, 8:01 a.m.