Triple
T25788697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rail Passengers Council |
E649489
|
entity |
| Predicate | regulatedSector |
P171737
|
FINISHED |
| Object | railway passenger services |
—
|
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: railway passenger services | Statement: [Rail Passengers Council, regulatedSector, railway passenger services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regulatedSector Context triple: [Rail Passengers Council, regulatedSector, railway passenger services]
-
A.
ownerSector
Indicates the sector or industry category to which the owner of an entity belongs.
-
B.
includesIndependentSector
Indicates that something encompasses or contains the independent (non-governmental, nonprofit) sector as part of its scope or composition.
-
C.
notableSector
Indicates that an entity is particularly prominent, influential, or significant within a specified sector or industry.
-
D.
nonProfitSector
Indicates that an entity operates within or is associated with the nonprofit sector, typically focusing on mission-driven rather than profit-driven activities.
-
E.
typicalConstituentSector
Indicates that something is a usual or characteristic sector that forms part of a larger whole or system.
- 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_69e7ab33e9308190afe415dc6f9e8876 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6a28c7c148190bfc980aad9f678ca |
completed | May 3, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69f69fe1e3c88190830bb2e9f407357e |
completed | May 3, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69f6a28b8ea881908733485374771c51 |
completed | May 3, 2026, 1:19 a.m. |
Created at: April 22, 2026, 5:57 a.m.