Triple
T33649323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duncan |
E862046
|
entity |
| Predicate | previousFranchiseOwner |
P181200
|
FINISHED |
| Object | HIT Entertainment |
—
|
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: HIT Entertainment | Statement: [Duncan, previousFranchiseOwner, HIT Entertainment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: previousFranchiseOwner Context triple: [Duncan, previousFranchiseOwner, HIT Entertainment]
-
A.
previousFranchiseCity
Indicates that a city was formerly the home location of a particular franchise before it moved or relocated.
-
B.
previousFranchiseName
Indicates that an entity previously operated under a different franchise name, specifying what that earlier franchise name was.
-
C.
previousFranchise
Indicates that one franchise directly precedes another in a series or succession of related franchises.
-
D.
predecessorFranchise
Indicates that one franchise directly precedes and is succeeded by another franchise in a series or lineage.
-
E.
formerFranchise
chosen
Indicates that an entity previously held a franchise relationship with another entity but no longer does.
- 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_69f349840ba881908e3bfce536aeb92b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff109695008190a22b47ef8be2e3f9 |
completed | May 9, 2026, 10:46 a.m. |
| PD | Predicate disambiguation | batch_69ff0f243ea88190970d2c520b55c816 |
completed | May 9, 2026, 10:40 a.m. |
Created at: May 1, 2026, 1:42 a.m.