Triple
T14942748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cameron Roberts |
E372571
|
entity |
| Predicate | sexualOrientationInFiction |
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: [Cameron Roberts, sexualOrientationInFiction, gay]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sexualOrientationInFiction Context triple: [Cameron Roberts, sexualOrientationInFiction, 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.
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.
-
C.
sexualOrientationRevealedIn
Indicates that an entity’s sexual orientation is disclosed, made known, or becomes apparent within a specified context, medium, or situation.
-
D.
fictionalGender
Indicates that one entity has a gender identity or classification that exists only within a fictional or imaginary context.
-
E.
fictionalLover
Indicates a romantic partner or love interest that exists only within a fictional or imaginary context.
- 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded68c1df0819084c0cd61b207d398 |
completed | April 15, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69de9a588c2c8190b1245a1c406f447c |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:38 a.m.