Triple
T29922815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 天草飛行場 |
E759991
|
entity |
| Predicate | 地域名の由来 |
P103146
|
FINISHED |
| Object | 天草諸島に位置することから命名された |
—
|
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: 天草諸島に位置することから命名された | Statement: [天草飛行場, 地域名の由来, 天草諸島に位置することから命名された]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 地域名の由来 Context triple: [天草飛行場, 地域名の由来, 天草諸島に位置することから命名された]
-
A.
influenceOnToponymy
Indicates that one entity has affected or shaped the naming, form, or development of place names associated with another entity.
-
B.
hasToponymicMotivation
chosen
Indicates that something is motivated, derived, or named based on a place name (toponym).
-
C.
toponymLiteralMeaning
Indicates the literal or etymological meaning of a place name (toponym), describing what the name directly translates to or signifies.
-
D.
seaNameEtymology
Indicates the origin or derivation of the name given to a particular sea.
-
E.
legacyToponym
Indicates that one place name is an older or former name historically used to refer to the same geographic entity as another place name.
- 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_69f2246189fc8190996b63ee1f9a2374 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f677953ad0819099fa0d8006a65679 |
completed | May 2, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69f66ec8298c8190b41fe9d182c05676 |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 29, 2026, 6:15 p.m.