Triple
T11584853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marceline the Vampire Queen |
E274722
|
entity |
| Predicate | canonicalSexuality |
P4324
|
FINISHED |
| Object | bisexual |
—
|
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: bisexual | Statement: [Marceline the Vampire Queen, canonicalSexuality, bisexual]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canonicalSexuality Context triple: [Marceline the Vampire Queen, canonicalSexuality, bisexual]
-
A.
hasSexualityCharacteristic
Indicates that an entity possesses a specific sexual orientation or sexuality-related characteristic.
-
B.
sexualOrientation
chosen
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.
sexes
Indicates that one entity engages in sexual activity with another entity.
-
D.
standardSex
Indicates that two entities share the same biological sex or gender classification.
-
E.
coneSex
Indicates a sexual or mating relationship involving a cone-shaped structure or entity.
- 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_69d6aae6b14c81908dc5a74bad7591f9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d89462203881908870e991a5b21770 |
completed | April 10, 2026, 6:10 a.m. |
| PD | Predicate disambiguation | batch_69d85dcbacd0819094d4a1237055affa |
completed | April 10, 2026, 2:17 a.m. |
Created at: April 8, 2026, 9:38 p.m.