Triple
T33648922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Edwards |
E862037
|
entity |
| Predicate | partOfFranchiseOrigin |
P201568
|
FINISHED |
| Object | Thomas & Friends |
—
|
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: Thomas & Friends | Statement: [Peter Edwards, partOfFranchiseOrigin, Thomas & Friends]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfFranchiseOrigin Context triple: [Peter Edwards, partOfFranchiseOrigin, Thomas & Friends]
-
A.
originalFranchiseOf
Indicates that one entity is the source or originating franchise from which another franchise, adaptation, or derivative work is based or derived.
-
B.
partOfFranchiseLineage
Indicates that one entity belongs to, or is derived from, the same overarching franchise lineage as another entity, reflecting continuity within a shared franchise.
-
C.
partOfFranchiseOrAdaptations
Indicates that one work belongs to the same franchise as another work or is an adaptation derived from it.
-
D.
originalFranchiseName
Indicates that an entity is associated with the name of the franchise from which it originally comes or to which it originally belongs.
-
E.
partOfFranchiseWithWork
Indicates that one work belongs to, or is included within, the same franchise as another work.
- F. None of above. chosen
Provenance (4 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_6a00053d8004819097ad9cf6431a20a3 |
completed | May 10, 2026, 4:10 a.m. |
| PD | Predicate disambiguation | batch_6a0004b3a82c81908e2bf9a533a93eb6 |
completed | May 10, 2026, 4:08 a.m. |
| PDg | Predicate description generation | batch_6a00053cdcb08190980df73e235e9ad8 |
completed | May 10, 2026, 4:10 a.m. |
Created at: May 1, 2026, 1:42 a.m.