Triple
T31250639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yokosuka aircraft |
E796806
|
entity |
| Predicate | geographicLocationOfDesign |
P45143
|
FINISHED |
| Object | Yokosuka, Kanagawa, Japan |
—
|
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: Yokosuka, Kanagawa, Japan | Statement: [Yokosuka aircraft, geographicLocationOfDesign, Yokosuka, Kanagawa, Japan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: geographicLocationOfDesign Context triple: [Yokosuka aircraft, geographicLocationOfDesign, Yokosuka, Kanagawa, Japan]
-
A.
designLocation
chosen
Indicates the place or setting where something is conceived, planned, or designed.
-
B.
designedForLocation
Indicates that something has been created or configured specifically to be used in, or suited to, a particular location.
-
C.
designedIn
Indicates that something was created, planned, or conceived during a particular time period or at a specific location.
-
D.
locatedIn
Indicates that one entity exists or is situated within the spatial, administrative, or conceptual boundaries of another entity.
-
E.
countryOfDesignActivity
Indicates the country in which the design-related activity associated with an entity takes place or is carried out.
- 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_69f224dc84d0819081f1cb6f9127e6b1 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f7516d5b4081908588a6feb541f355 |
completed | May 3, 2026, 1:45 p.m. |
| PD | Predicate disambiguation | batch_69f74d40ebb081909daf60623e38f41d |
completed | May 3, 2026, 1:27 p.m. |
Created at: April 29, 2026, 9:11 p.m.