Triple
T24901369
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thames Trains |
E623585
|
entity |
| Predicate | accidentConsequences |
P34334
|
FINISHED |
| Object | major safety review of UK rail signalling and operations |
—
|
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: major safety review of UK rail signalling and operations | Statement: [Thames Trains, accidentConsequences, major safety review of UK rail signalling and operations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: accidentConsequences Context triple: [Thames Trains, accidentConsequences, major safety review of UK rail signalling and operations]
-
A.
consequenceOfCollision
Indicates that one event, state, or condition occurs as a direct result of a collision between entities.
-
B.
resultOfAccident
chosen
Indicates that something exists or occurs as a consequence or outcome of an accident.
-
C.
accident
Indicates an unintended, unforeseen event or mishap occurring, often resulting in damage, injury, or disruption.
-
D.
accidentSeverity
Indicates the level or degree of seriousness associated with an accident.
-
E.
causedAccident
Indicates that one entity is responsible for bringing about or initiating an accident involving another entity or situation.
- 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_69e2fac797cc8190b30d77f4121099ac |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f44a417a58819081777e18dda149fd |
completed | May 1, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69f442b8479c8190a7c8e416ac9e28a0 |
completed | May 1, 2026, 6:05 a.m. |
Created at: April 18, 2026, 5:27 a.m.