Triple
T32210794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angie Jordan |
E822795
|
entity |
| Predicate | hasTelevisionShowWithinFiction |
P57669
|
FINISHED |
| Object | Queen of Jordan |
—
|
NE NERFINISHED |
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: Queen of Jordan | Statement: [Angie Jordan, hasTelevisionShowWithinFiction, Queen of Jordan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTelevisionShowWithinFiction Context triple: [Angie Jordan, hasTelevisionShowWithinFiction, Queen of Jordan]
-
A.
hasFictionalShowWithinShow
chosen
Indicates that one show contains or features another fictional show within its narrative.
-
B.
hasTVShowWithinFilm
Indicates that a film contains or features a television show within its narrative or structure.
-
C.
hasFictionalWork
Indicates that one entity is the creator, owner, or source of a fictional work associated with another entity.
-
D.
hasFictionalFilmWithinPlay
Indicates that within a theatrical play, there is a fictional film that exists or is depicted as part of the play’s narrative or structure.
-
E.
formedInTelevisionShow
Indicates that an entity (such as a group, band, or organization) came into existence or was created within the context or storyline of a particular television show.
- 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_69f3490a3bec819097bc58d4731b9d08 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd37b695c88190855801626f91c4cd |
completed | May 8, 2026, 1:09 a.m. |
| PD | Predicate disambiguation | batch_69fd374cccf08190a230e87164af5938 |
completed | May 8, 2026, 1:07 a.m. |
Created at: May 1, 2026, 12:37 a.m.