Triple
T6271510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Will & Grace |
E140543
|
entity |
| Predicate | hasLGBTQThemes |
P45364
|
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: [Will & Grace, hasLGBTQThemes, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLGBTQThemes Context triple: [Will & Grace, hasLGBTQThemes, true]
-
A.
hasLGBTTheme
chosen
Indicates that the subject includes, features, or centrally involves lesbian, gay, bisexual, or transgender themes or issues.
-
B.
LGBTWing
Indicates that an entity is a subgroup, faction, or organizational wing specifically focused on LGBT (lesbian, gay, bisexual, and transgender) issues or representation.
-
C.
isOpenlyLGBT
Indicates that an entity publicly identifies as lesbian, gay, bisexual, transgender, or otherwise part of the LGBT community.
-
D.
hasPersonalThemes
Indicates that something (such as a work, message, or expression) involves themes that are personal, intimate, or directly related to an individual’s own experiences or inner life.
-
E.
followsInTheme
Indicates that one element continues or succeeds another while maintaining the same theme or thematic 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_69c008cabc4081909723e2547c9d6cc0 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063bb340c8190ab81b249cefa91ca |
completed | March 22, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69c05606fb50819082d1a5a91e5030b6 |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:25 p.m.