Triple
T19453611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TRANSform Me |
E486678
|
entity |
| Predicate | hasTransgenderRepresentation |
P88125
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [TRANSform Me, hasTransgenderRepresentation, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTransgenderRepresentation Context triple: [TRANSform Me, hasTransgenderRepresentation, true]
-
A.
hasGenderRepresentation
Indicates that something includes, reflects, or portrays one or more genders within its content, structure, or composition.
-
B.
hasLGBTCharacter
chosen
Indicates that the subject includes, features, or is associated with one or more characters who identify as lesbian, gay, bisexual, or transgender.
-
C.
hasGenderIdentity
Indicates that an entity identifies with or experiences a particular gender.
-
D.
publiclyCameOutAsTransgender
Indicates that a person has openly and publicly disclosed that they are transgender.
-
E.
hasLGBTTheme
Indicates that the subject includes, features, or centrally involves lesbian, gay, bisexual, or transgender themes or issues.
- 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6339407a08190a3e0213bfbb4df3d |
completed | April 20, 2026, 2:09 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7499a4819082bec0be8afba35c |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:38 p.m.