Triple
T29293822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miyazaki–Tokyo Haneda |
E742760
|
entity |
| Predicate | locatedInSameCountryAs |
P201652
|
FINISHED |
| Object | Tokyo–Osaka route |
—
|
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: Tokyo–Osaka route | Statement: [Miyazaki–Tokyo Haneda, locatedInSameCountryAs, Tokyo–Osaka route]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInSameCountryAs Context triple: [Miyazaki–Tokyo Haneda, locatedInSameCountryAs, Tokyo–Osaka route]
-
A.
locatedInCurrentCountry
Indicates that an entity is situated within the geographic boundaries of the country in which it is presently found.
-
B.
alsoInCountry
Indicates that something located in one country is additionally located or present in another specified country.
-
C.
meetsInCountry
Indicates that two or more entities have an in-person meeting that takes place within the specified country.
-
D.
existsInConstituentCountry
Indicates that one entity is located within or is present in a country that is a constituent part of a larger sovereign state.
-
E.
memberOfThroughCountry
Indicates that an entity is a member of another entity (such as an organization or group) by virtue of, or via, its association with a specific country.
- 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_69f0912323c48190b9a24ef8cf359225 |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_6a0010e46d948190a51111b5270fade7 |
completed | May 10, 2026, 5 a.m. |
| PD | Predicate disambiguation | batch_6a001061d34c8190bfe73f3d7c061eb7 |
completed | May 10, 2026, 4:58 a.m. |
| PDg | Predicate description generation | batch_6a0010e304a08190a4d0a4fa11a9a3b3 |
completed | May 10, 2026, 5 a.m. |
Created at: April 28, 2026, 1:04 p.m.