Triple
T10857910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London public transport network |
E256316
|
entity |
| Predicate | primaryFundingSources |
P67
|
FINISHED |
| Object | fares |
—
|
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: fares | Statement: [London public transport network, primaryFundingSources, fares]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryFundingSources Context triple: [London public transport network, primaryFundingSources, fares]
-
A.
secondaryFundingSource
Indicates that an entity has an additional, non-primary source of financial support or funding.
-
B.
fundedBy
chosen
Indicates that an entity receives financial support or resources from another entity.
-
C.
fundingFocus
Indicates that one entity’s funding is directed toward or prioritized for a particular target, theme, or area of activity.
-
D.
fundingContext
Indicates the circumstances, purpose, or conditions under which funding is provided or used in a given relationship or action.
-
E.
primaryBeneficiaries
Indicates which entities are the main recipients or advantaged parties resulting from a particular action, resource, or arrangement.
- 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_69d6aa83d1448190a66d93c32394d21f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d751377da88190a7244bb9d6b0c2ec |
completed | April 9, 2026, 7:11 a.m. |
| PD | Predicate disambiguation | batch_69d70d308dfc81908792f98cfb871392 |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:20 p.m.