Triple
T37061156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 高槻駅 |
E917326
|
entity |
| Predicate | 接続先都市 |
P180202
|
FINISHED |
| Object | 大阪市方面 |
—
|
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: 大阪市方面 | Statement: [高槻駅, 接続先都市, 大阪市方面]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 接続先都市 Context triple: [高槻駅, 接続先都市, 大阪市方面]
-
A.
primaryCityAtOtherEnd
Indicates that a given city is the main or principal city located at the opposite end of a specified route, connection, or relationship from another city.
-
B.
otherCity
Indicates that one city is different from and not the same as another city.
-
C.
linkedCity
Indicates that two entities are associated with each other through a specific city, such as being located in, connected via, or related by that city.
-
D.
servesAsFocusCityFor
Indicates that a city functions as a primary or designated focus city for an airline, organization, or transportation network, typically hosting significant but not hub-level operations or activities.
-
E.
connectsRegionalCity
chosen
Indicates a relationship where one entity serves as a link or transport route between a regional city and another location.
- 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_69f76e95fa40819091e14681087ae5e4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb34e5576881909394355c8ec6ddd2 |
completed | May 6, 2026, 12:32 p.m. |
| PD | Predicate disambiguation | batch_69fb2f6171e88190bf1e0ee6a644b6a9 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 3, 2026, 4:14 p.m.