Triple
T25211350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jefferson Cleaners |
E631695
|
entity |
| Predicate | usedAsBackstoryIn |
P105687
|
FINISHED |
| Object | All in the Family |
—
|
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: All in the Family | Statement: [Jefferson Cleaners, usedAsBackstoryIn, All in the Family]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedAsBackstoryIn Context triple: [Jefferson Cleaners, usedAsBackstoryIn, All in the Family]
-
A.
hasFictionalBackstory
Indicates that an entity is associated with an invented or imaginary narrative background rather than a real-world history.
-
B.
expandsBackstoryOf
Indicates that one entity provides additional background details or context that elaborate on the history or origins of another entity.
-
C.
usedInFictionalWork
chosen
Indicates that something (such as a concept, object, or character) appears or is employed within a specific fictional work.
-
D.
roleInCharacterBackstory
Indicates that one entity plays a specific role or part in shaping another entity’s character backstory or personal history.
-
E.
originStoryIncludes
Indicates that an entity’s origin story contains, involves, or features the referenced element as a component or part of that backstory.
- 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_69e75a8d1aa48190a4320acd3654762c |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f621fcea1481909b6f8b3af1ee6820 |
completed | May 2, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69f620dc38088190b56b2b15ed75b3c2 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 21, 2026, 12:58 p.m.