Triple
T22993285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British Rail Class 455 |
E572112
|
entity |
| Predicate | operatorSector |
P67916
|
FINISHED |
| Object | commuter rail in South East England |
—
|
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: commuter rail in South East England | Statement: [British Rail Class 455, operatorSector, commuter rail in South East England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatorSector Context triple: [British Rail Class 455, operatorSector, commuter rail in South East England]
-
A.
ownerSector
Indicates the sector or industry category to which the owner of an entity belongs.
-
B.
economicSectors
Indicates a relationship that associates entities with the economic sectors or industries in which they operate or to which they belong.
-
C.
sector
Indicates that an entity operates in, belongs to, or is associated with a particular economic or industrial sector.
-
D.
typicalConstituentSector
Indicates that something is a usual or characteristic sector that forms part of a larger whole or system.
-
E.
operatorIndustry
chosen
Indicates that an operator (such as a company or organization) is engaged in or associated with a particular industry sector.
- 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_69e245b535808190adef8a9df3c584db |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f182f017a88190b02d0649a3af5d99 |
completed | April 29, 2026, 4:02 a.m. |
| PD | Predicate disambiguation | batch_69ef3b974e7c8190b8be11dbb4518693 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:50 p.m.