Triple
T12859731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carol |
E307551
|
entity |
| Predicate | LGBTRepresentation |
P88125
|
FINISHED |
| Object | lesbian main characters |
—
|
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: lesbian main characters | Statement: [Carol, LGBTRepresentation, lesbian main characters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: LGBTRepresentation Context triple: [Carol, LGBTRepresentation, lesbian main characters]
-
A.
hasLGBTCharacter
chosen
Indicates that the subject includes, features, or is associated with one or more characters who identify as lesbian, gay, bisexual, or transgender.
-
B.
hasLGBTTheme
Indicates that the subject includes, features, or centrally involves lesbian, gay, bisexual, or transgender themes or issues.
-
C.
LGBTWing
Indicates that an entity is a subgroup, faction, or organizational wing specifically focused on LGBT (lesbian, gay, bisexual, and transgender) issues or representation.
-
D.
isOpenlyLGBT
Indicates that an entity publicly identifies as lesbian, gay, bisexual, transgender, or otherwise part of the LGBT community.
-
E.
representsPeople
Indicates that one entity serves as a representation or stand-in for one or more people.
- 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_69d7bdf5e7cc8190be357278bc5ba3bb |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9714208f881908f7f8a921362909a |
completed | April 10, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69d96fa3002881908000357b1f95a3ac |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:37 p.m.