Triple
T35568851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MMB |
E1027853
|
entity |
| Predicate | hasNearbyCityServed |
P83632
|
FINISHED |
| Object | Abashiri |
—
|
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: Abashiri | Statement: [MMB, hasNearbyCityServed, Abashiri]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyCityServed Context triple: [MMB, hasNearbyCityServed, Abashiri]
-
A.
nearbyCityServed
chosen
Indicates that a city is geographically close enough to another city to be considered within its service or support area.
-
B.
hasNearbyCityFunction
Indicates that one entity serves as a nearby urban center or city-like service hub for another entity.
-
C.
nearbyAreaServed
Indicates that a location or entity provides services or coverage to an adjacent or nearby area.
-
D.
belongsToCityServedBy
Indicates that something is associated with or part of the city that is served by a particular service, facility, or infrastructure.
-
E.
associatedCityServed
Indicates that there is a relationship where a service, facility, or entity is linked to and serves a particular city.
- 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_69f76e020fd8819081cb080e7e203083 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a002103c93081908398fa5726f5fa6e |
completed | May 10, 2026, 6:09 a.m. |
| PD | Predicate disambiguation | batch_6a001fcb9fb48190a27d8f2ca983fbe6 |
completed | May 10, 2026, 6:03 a.m. |
Created at: May 3, 2026, 4:04 p.m.