Triple
T29771875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lac-Mégantic |
E755269
|
entity |
| Predicate | railDisasterType |
P1788
|
FINISHED |
| Object | crude oil train derailment and explosion |
—
|
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: crude oil train derailment and explosion | Statement: [Lac-Mégantic, railDisasterType, crude oil train derailment and explosion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railDisasterType Context triple: [Lac-Mégantic, railDisasterType, crude oil train derailment and explosion]
-
A.
railDisasterYear
Indicates the year in which a rail-related disaster occurred.
-
B.
accidentType
chosen
Indicates the specific category or kind of accident associated with an event or incident.
-
C.
deadliestRailAccidentInJapanSince
Indicates that a rail accident is the most lethal one in Japan occurring on or after a specified date or event.
-
D.
notableDisasterType
Indicates the specific kind or category of disaster for which something (such as a place, event, or entity) is notable or best known.
-
E.
numberOfCarsDerailed
Indicates the count of cars that have come off the tracks in a derailment incident.
- 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_69f0ef878574819088c867fd1a5c8b86 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f67462f1a881909b30f47ed3f14e05 |
completed | May 2, 2026, 10:02 p.m. |
| PD | Predicate disambiguation | batch_69f66ec5bf508190ad088b89455252bd |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 28, 2026, 8:43 p.m.