Triple
T35532441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Happy, Texas |
E1026836
|
entity |
| Predicate | hasLGBTElement |
P88125
|
FINISHED |
| Object | features characters posing as gay men |
—
|
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: features characters posing as gay men | Statement: [Happy, Texas, hasLGBTElement, features characters posing as gay men]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLGBTElement Context triple: [Happy, Texas, hasLGBTElement, features characters posing as gay men]
-
A.
hasLGBTTheme
Indicates that the subject includes, features, or centrally involves lesbian, gay, bisexual, or transgender themes or issues.
-
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.
hasLGBTParents
Indicates that an individual has one or more parents who identify as lesbian, gay, bisexual, or transgender.
-
D.
isOpenlyLGBT
Indicates that an entity publicly identifies as lesbian, gay, bisexual, transgender, or otherwise part of the LGBT community.
-
E.
isLGBTFamilyAdvocate
Indicates that an entity actively supports, promotes, or defends the rights and well-being of LGBT individuals and their families.
- 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_69f76dff7e508190b28ceeee770dce23 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79a54aa3c8190b2bb5d790b2d42d4 |
completed | May 3, 2026, 6:56 p.m. |
| PD | Predicate disambiguation | batch_69f7961970408190b669cc556e30a608 |
completed | May 3, 2026, 6:38 p.m. |
Created at: May 3, 2026, 4:04 p.m.