Triple
T33404652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gordy's Home |
E855404
|
entity |
| Predicate | fictionalWithinWorkOf |
P182578
|
FINISHED |
| Object | Jordan Peele film Nope |
—
|
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: Jordan Peele film Nope | Statement: [Gordy's Home, fictionalWithinWorkOf, Jordan Peele film Nope]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalWithinWorkOf Context triple: [Gordy's Home, fictionalWithinWorkOf, Jordan Peele film Nope]
-
A.
isFictionalWorkWithinWork
chosen
Indicates that one fictional work is contained or presented as a subordinate or embedded work within another fictional work.
-
B.
possiblyFictionalWithinWork
Indicates that an entity may be fictional within the context of a specific work, rather than definitively real or definitively fictional there.
-
C.
worksWithInFiction
Indicates that two fictional characters are depicted as collaborating, interacting, or being associated with each other within a narrative work.
-
D.
isForFictionalWork
Indicates that something is intended to be used in, associated with, or specifically created for a fictional work.
-
E.
workInFiction
Indicates that one entity is a fictional work in which the other entity appears or is set.
- 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_69f3496e3f1c8190bcecfa82aa9d17ff |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fe6739d4dc8190ae7505c089bbac29 |
completed | May 8, 2026, 10:44 p.m. |
| PD | Predicate disambiguation | batch_69fe6541dffc81909c66a61ba69f38fc |
completed | May 8, 2026, 10:35 p.m. |
Created at: May 1, 2026, 1:36 a.m.