Triple
T424354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ECHL |
E8172
|
entity |
| Predicate | hasFranchiseModel |
P13614
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [ECHL, hasFranchiseModel, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFranchiseModel Context triple: [ECHL, hasFranchiseModel, yes]
-
A.
hadFranchise
Indicates that one entity possessed or operated a franchise right or franchise unit of another entity.
-
B.
franchiseOf
Indicates that one entity operates as a franchise belonging to or licensed by another entity.
-
C.
controlsFranchiseType
Indicates that one entity has authority to determine or manage the type or category of franchise associated with another entity.
-
D.
associatedFranchise
Indicates a relationship where one entity is linked to, or belongs within, a particular franchise or franchise universe.
-
E.
basisOfFranchise
Indicates that one work or property serves as the foundational source or origin for a broader franchise or series.
- 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_69a2e7f1d1bc81909cf2dc9754a3c334 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eed3e4cc8190ba6aff3bd1adb06f |
completed | Feb. 28, 2026, 1:34 p.m. |
| PD | Predicate disambiguation | batch_69a2edd5439c8190aea661b8b4aa51e9 |
completed | Feb. 28, 2026, 1:29 p.m. |
| PDg | Predicate description generation | batch_69a2ee8b56d08190bd625626353d01b4 |
completed | Feb. 28, 2026, 1:32 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.