Triple
T25715435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London–Tokyo |
E644848
|
entity |
| Predicate | isSubjectToBilateralAirServiceAgreements |
P161473
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [London–Tokyo, isSubjectToBilateralAirServiceAgreements, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isSubjectToBilateralAirServiceAgreements Context triple: [London–Tokyo, isSubjectToBilateralAirServiceAgreements, true]
-
A.
haveCrossBorderAgreements
Indicates that there exist formal agreements or arrangements between entities that operate across national or jurisdictional borders.
-
B.
haveCulturalExchangeAgreements
Indicates that two entities are formally engaged in mutual cultural exchange through established agreements or partnerships.
-
C.
internationalAgreementBasis
Indicates that one entity serves as the legal or formal basis for an international agreement involving another entity.
-
D.
hasFreeTradeAgreement
Indicates that two entities are linked by a formal free trade agreement that reduces or eliminates trade barriers between them.
-
E.
allowsVisaFreeAccessFor
Indicates that one party grants another the ability to enter or stay in its territory without requiring a visa.
- 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_69e77e8476fc8190bd5e9d05b89fad0a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f613bc641c819084343cc78d080640 |
completed | May 2, 2026, 3:09 p.m. |
| PD | Predicate disambiguation | batch_69f611a72780819082f44e66ca2c6ac9 |
completed | May 2, 2026, 3 p.m. |
| PDg | Predicate description generation | batch_69f613502d808190b89927e5e734b43a |
completed | May 2, 2026, 3:08 p.m. |
Created at: April 21, 2026, 9:40 p.m.