Triple
T24296848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | System One travelcards |
E605982
|
entity |
| Predicate | coversOperatorType |
P155460
|
FINISHED |
| Object | multiple operators |
—
|
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: multiple operators | Statement: [System One travelcards, coversOperatorType, multiple operators]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coversOperatorType Context triple: [System One travelcards, coversOperatorType, multiple operators]
-
A.
typicalOperatorType
Indicates the usual or most common type or category of operator associated with a given entity or context.
-
B.
involvesOperator
Indicates that a given process, action, or relationship includes or makes use of a specific operator as a participating element.
-
C.
coversActionType
Indicates that one entity’s scope, responsibility, or applicability includes or encompasses a particular type of action.
-
D.
typicalOperator
Indicates that an entity commonly or normally performs operations on, or acts upon, another entity in a standard or expected manner.
-
E.
isOperatorOn
Indicates that one entity serves as an operator responsible for operating, controlling, or managing another entity (such as a system, machine, or process).
- F. None of above. chosen
Provenance (4 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_69e29549335881909cbf27adcaba1cf0 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f2915ada688190aa9c4bdaa2f1617f |
completed | April 29, 2026, 11:16 p.m. |
| PD | Predicate disambiguation | batch_69f1c45c6ec081908401b69424428100 |
completed | April 29, 2026, 8:42 a.m. |
| PDg | Predicate description generation | batch_69f1c6d4e99081909f61899eccafb73e |
completed | April 29, 2026, 8:52 a.m. |
Created at: April 18, 2026, 12:09 a.m.