Triple
T19107109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nevsky Express |
E467683
|
entity |
| Predicate | 2009AccidentInjuries |
P25887
|
FINISHED |
| Object | dozens of passengers |
—
|
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: dozens of passengers | Statement: [Nevsky Express, 2009AccidentInjuries, dozens of passengers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 2009AccidentInjuries Context triple: [Nevsky Express, 2009AccidentInjuries, dozens of passengers]
-
A.
resultOfAccident
Indicates that something exists or occurs as a consequence or outcome of an accident.
-
B.
injuredIn
Indicates that an entity sustained an injury as a result of a specified event, situation, or action.
-
C.
accident
Indicates an unintended, unforeseen event or mishap occurring, often resulting in damage, injury, or disruption.
-
D.
involvedInAccident
Indicates that an entity participated in, was affected by, or was otherwise a party to a specific accident or collision event.
-
E.
injuriesApprox
chosen
Indicates an approximate or estimated number or extent of injuries associated with an event or entity.
- 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_69d8dd06a26481908039e2a1bae8c597 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e391245c8190b1393577b61c4f76 |
completed | April 20, 2026, 8:28 a.m. |
| PD | Predicate disambiguation | batch_69e4b9ac41848190afd0f33b42cebe99 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:04 p.m.