Triple
T30931981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS239 |
E788017
|
entity |
| Predicate | servesTownType |
P57766
|
FINISHED |
| Object | mountain towns |
—
|
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: mountain towns | Statement: [SS239, servesTownType, mountain towns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesTownType Context triple: [SS239, servesTownType, mountain towns]
-
A.
servesTownship
Indicates that an entity provides official services or administrative functions to a particular township.
-
B.
cityServedType
chosen
Indicates the type or category of city that is served by a given entity (such as a facility, service, or infrastructure).
-
C.
townServed
Indicates that a given service, facility, or infrastructure serves or provides coverage to a particular town.
-
D.
servesType
Indicates that one entity provides, offers, or is used to deliver a particular type, category, or kind of thing or service.
-
E.
servesCountyTown
Indicates that an entity (such as a service, office, or facility) provides coverage or service to a specified county or town.
- 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_69f224c0b7fc819090cb89df60d23653 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe9fb9735c8190a360b556c9d00b3f |
completed | May 9, 2026, 2:45 a.m. |
| PD | Predicate disambiguation | batch_69fe9eaa88008190a9b2a469dc685002 |
completed | May 9, 2026, 2:40 a.m. |
Created at: April 29, 2026, 8:52 p.m.