Triple
T26642650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Commissioner for Infrastructure and Energy |
E668821
|
entity |
| Predicate | typicalSectorsCovered |
P133297
|
FINISHED |
| Object | transport |
—
|
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: transport | Statement: [Commissioner for Infrastructure and Energy, typicalSectorsCovered, transport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSectorsCovered Context triple: [Commissioner for Infrastructure and Energy, typicalSectorsCovered, transport]
-
A.
sectoralCoverage
Indicates the specific sectors, industries, or domains to which something (such as a policy, agreement, or dataset) applies or extends.
-
B.
typicalConstituentSector
chosen
Indicates that something is a usual or characteristic sector that forms part of a larger whole or system.
-
C.
economicSectors
Indicates a relationship that associates entities with the economic sectors or industries in which they operate or to which they belong.
-
D.
targetsSector
Indicates that an entity is directed toward, focused on, or intended to affect a particular economic or industry sector.
-
E.
supportedIndustry
Indicates that one entity provides backing, resources, or services to help sustain or advance a particular industry.
- 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_69ee9d00eb5481908d6c6d0ada2f0c9a |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69feced53a7c819098ec474fb7d514b0 |
completed | May 9, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69fecd9cd5288190aac8b4e04a7ee78e |
completed | May 9, 2026, 6:01 a.m. |
Created at: April 27, 2026, 2:29 a.m.