Triple
T109708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fife Circle services |
E2218
|
entity |
| Predicate | primaryCouncilAreaServed |
P82
|
FINISHED |
| Object | Fife Council area |
—
|
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: Fife Council area | Statement: [Fife Circle services, primaryCouncilAreaServed, Fife Council area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryCouncilAreaServed Context triple: [Fife Circle services, primaryCouncilAreaServed, Fife Council area]
-
A.
areaServed
chosen
Indicates the geographic region or jurisdiction within which a service, organization, or activity is provided or applicable.
-
B.
sectorServed
Indicates the industry or economic sector that an entity primarily serves or targets with its activities, products, or services.
-
C.
primaryServes
Indicates that one entity’s main or principal function is to serve, support, or provide service to another entity.
-
D.
serviceAreaCharacteristic
Indicates a relationship where a service area is associated with a specific attribute or feature that characterizes it.
-
E.
servedCity
Indicates that a service, route, or facility operates in, reaches, or is available to 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_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a25711f6788190a22252ea3a3af394 |
completed | Feb. 28, 2026, 2:46 a.m. |
| PD | Predicate disambiguation | batch_69a2563fd2fc819090265edbfe3092d6 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.