Triple
T25715399
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London–Tokyo |
E644848
|
entity |
| Predicate | isMajorRouteBetweenCapitals |
P167267
|
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, isMajorRouteBetweenCapitals, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMajorRouteBetweenCapitals Context triple: [London–Tokyo, isMajorRouteBetweenCapitals, true]
-
A.
hasMajorCityOnRoute
Indicates that a major city lies along, or is directly served by, a specified route or path between locations.
-
B.
governingCountryCapitalConnectedTo
Indicates that the capital city of the governing country is directly connected (e.g., via infrastructure, transport, or communication links) to the referenced location or entity.
-
C.
hasCountryCapitalConnection
Indicates a relationship in which a specific country is associated with its official capital city.
-
D.
regionCapitalConnected
Indicates that a capital city is directly connected (e.g., by transport or infrastructure) to its surrounding region.
-
E.
isNeighboringCityOf
Indicates that one city is geographically adjacent to or directly borders another city.
- 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_69f66a6468ec8190a43ed6cd8c797f42 |
completed | May 2, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f66598d6008190a7ca8ff80399fd34 |
completed | May 2, 2026, 8:59 p.m. |
| PDg | Predicate description generation | batch_69f6691da93081909deaf680614fc900 |
completed | May 2, 2026, 9:14 p.m. |
Created at: April 21, 2026, 9:40 p.m.