Triple
T26803831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nick Salter |
E671170
|
entity |
| Predicate | hasFictionalSexualOrientation |
P113259
|
FINISHED |
| Object | gay |
—
|
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: gay | Statement: [Nick Salter, hasFictionalSexualOrientation, gay]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalSexualOrientation Context triple: [Nick Salter, hasFictionalSexualOrientation, gay]
-
A.
fictionalSexualOrientation
chosen
Indicates that one entity has a sexual orientation that exists only within a fictional or imagined context, rather than in real life.
-
B.
hasSexualityCharacteristic
Indicates that an entity possesses a specific sexual orientation or sexuality-related characteristic.
-
C.
fictionalGender
Indicates that one entity has a gender identity or classification that exists only within a fictional or imaginary context.
-
D.
hasLGBTCharacter
Indicates that the subject includes, features, or is associated with one or more characters who identify as lesbian, gay, bisexual, or transgender.
-
E.
sexualOrientation
Indicates an entity’s enduring pattern of romantic or sexual attraction toward others, typically in terms of the genders or sexes to which it is attracted.
- 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_69eeb31fbd888190a82dac5822e453bc |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f760a35b988190904e6267553ad2fe |
completed | May 3, 2026, 2:50 p.m. |
| PD | Predicate disambiguation | batch_69f75eb3d6f081908c933474eb359e3d |
completed | May 3, 2026, 2:41 p.m. |
Created at: April 27, 2026, 4:25 a.m.