Triple
T38463310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seoul Dynasty |
E912502
|
entity |
| Predicate | cityBasedFranchise |
P187180
|
FINISHED |
| Object | Seoul |
—
|
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: Seoul | Statement: [Seoul Dynasty, cityBasedFranchise, Seoul]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityBasedFranchise Context triple: [Seoul Dynasty, cityBasedFranchise, Seoul]
-
A.
cityBasedFranchises
chosen
Indicates that the franchises are located in, operate from, or are primarily associated with a particular city.
-
B.
hasFranchiseFromCity
Indicates that an entity holds a franchise or licensed operation originating from, or granted by, a particular city.
-
C.
franchisePlacement
Indicates that a franchise is established or located at a particular place or within a specific market area.
-
D.
franchiseConnection
Indicates a relationship where one entity is part of, derived from, or otherwise officially linked to a larger franchise or brand.
-
E.
franchiseOf
Indicates that one entity operates as a franchise belonging to or licensed by another entity.
- 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_69f76e861d8c81908559031dc66e3c15 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fcce7afcd08190906cc3801152656a |
completed | May 7, 2026, 5:40 p.m. |
| PD | Predicate disambiguation | batch_69fcccf140ec8190862d53388a5f40d7 |
completed | May 7, 2026, 5:33 p.m. |
Created at: May 3, 2026, 4:31 p.m.