Triple
T37005759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ora Baxter |
E915790
|
entity |
| Predicate | isFictionalInMedium |
P116013
|
FINISHED |
| Object | film or television production |
—
|
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: film or television production | Statement: [Ora Baxter, isFictionalInMedium, film or television production]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isFictionalInMedium Context triple: [Ora Baxter, isFictionalInMedium, film or television production]
-
A.
isFictionalCharacter
chosen
Indicates that the subject is a character that exists only in fiction rather than in real life.
-
B.
hasFictionalType
Indicates that an entity is associated with or classified under a particular type or category that is fictional rather than real.
-
C.
isSetInFictionalUniverse
Indicates that a narrative work takes place within a specific fictional universe or setting.
-
D.
livesInFiction
Indicates that one entity exists or resides within the fictional world or narrative setting created by another entity.
-
E.
isFictionalPersonFrom
Indicates that a fictional person originates from or is associated with a particular place or source.
- 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_69f76e90ed548190b187d2475f5c807d |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb154c0fe08190a2e41e7a29b6055f |
completed | May 6, 2026, 10:17 a.m. |
| PD | Predicate disambiguation | batch_69f9fecc005c8190be082a8689193745 |
completed | May 5, 2026, 2:29 p.m. |
Created at: May 3, 2026, 4:14 p.m.