Triple
T109697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fife Circle services |
E2218
|
entity |
| Predicate | operatorType |
P179
|
FINISHED |
| Object | franchised train operating company |
—
|
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: franchised train operating company | Statement: [Fife Circle services, operatorType, franchised train operating company]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatorType Context triple: [Fife Circle services, operatorType, franchised train operating company]
-
A.
operator
chosen
Indicates that one entity functions as the operator (controller or handler) of another entity, such as a system, device, or process.
-
B.
typeOfOperation
Indicates the specific kind or category of operation being performed or referenced in a given context.
-
C.
operationType
Indicates the specific kind of operation or action being performed or recorded in the relationship between entities.
-
D.
operatesOver
Indicates that one entity performs actions or exerts functional control across, upon, or throughout another entity or domain.
-
E.
operatesBy
Indicates that an entity performs its function, action, or process through the use or application of another entity (e.g., a method, mechanism, or principle).
- 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.