Triple
T32210800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angie Jordan |
E822795
|
entity |
| Predicate | networkWithinFiction |
P116931
|
FINISHED |
| Object | NBC |
—
|
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: NBC | Statement: [Angie Jordan, networkWithinFiction, NBC]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: networkWithinFiction Context triple: [Angie Jordan, networkWithinFiction, NBC]
-
A.
networkInFiction
chosen
Indicates that one entity is a network (e.g., TV, radio, streaming) that appears or operates within the fictional context of another entity (such as a work, universe, or narrative).
-
B.
locationWithinFiction
Indicates that one fictional location is situated inside or contained within another fictional location.
-
C.
languageWithinFiction
Indicates that a language is used or exists within the context of a fictional work or fictional universe.
-
D.
eraWithinFiction
Indicates that a time period or era exists inside the narrative world or timeline of a fictional work.
-
E.
showWithinFiction
Indicates that one entity is depicted, referenced, or occurs as part of the fictional world or narrative context of another 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_69f3490a3bec819097bc58d4731b9d08 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f707f7959881908f037f0d6b1d0c36 |
completed | May 3, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69f700fc274c8190a128593dc7c7abd0 |
completed | May 3, 2026, 8:02 a.m. |
Created at: May 1, 2026, 12:37 a.m.