Triple
T26533106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sanford and Son junkyard |
E670872
|
entity |
| Predicate | businessTypeInFiction |
P121895
|
FINISHED |
| Object | family-owned junkyard |
—
|
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: family-owned junkyard | Statement: [Sanford and Son junkyard, businessTypeInFiction, family-owned junkyard]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: businessTypeInFiction Context triple: [Sanford and Son junkyard, businessTypeInFiction, family-owned junkyard]
-
A.
hasFictionalBusinessType
chosen
Indicates that an entity is associated with a type or category of fictional business it operates or represents.
-
B.
bodyTypeInFiction
Indicates how a particular body type is portrayed, characterized, or represented within fictional works.
-
C.
fictionalType
Indicates that one entity is a fictional or imaginary type or category of the other entity.
-
D.
createsInFiction
Indicates that one entity is the creator or originator of another entity within a fictional or narrative context.
-
E.
fictionalEntityType
Indicates that the subject is classified as a particular type or category of fictional entity within a narrative or imaginary context.
- 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_69eeb31ea1e08190b9ff43cf9bc25bf8 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f62d53ad58819080c5227c7a729d15 |
completed | May 2, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69f62c15952881908a5ea0c25904afec |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 1:37 a.m.