Triple
T38665101
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 京浜急行電鉄株式会社 |
E940432
|
entity |
| Predicate | 接続空港 |
P58803
|
FINISHED |
| Object | 東京国際空港 |
—
|
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: 東京国際空港 | Statement: [京浜急行電鉄株式会社, 接続空港, 東京国際空港]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 接続空港 Context triple: [京浜急行電鉄株式会社, 接続空港, 東京国際空港]
-
A.
connectsWithAirport
Indicates that there is a direct transportation or operational link established between an entity and an airport.
-
B.
associatedAirport
chosen
Indicates a relationship where an entity is linked or connected to a specific airport, typically as its relevant or corresponding airport.
-
C.
associatedHubAirport
Indicates that one entity serves as a primary or hub airport functionally linked to the other entity.
-
D.
hasAirportAccessTo
Indicates that one location or entity has direct access to another via an airport connection or service.
-
E.
airportServesAs
Indicates that an airport functions in a particular role or capacity (such as primary, secondary, or hub) for a specified area, organization, or service.
- 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_69f76edfde348190bf6529d9f49ecd62 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdfbc71c481908ba7f87907b17782 |
completed | May 7, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe580b8819087f143596b2c79c0 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 3, 2026, 4:33 p.m.