Triple
T29771879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lac-Mégantic |
E755269
|
entity |
| Predicate | railDisasterLedTo |
P169693
|
FINISHED |
| Object | changes in rail safety regulations in Canada |
—
|
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: changes in rail safety regulations in Canada | Statement: [Lac-Mégantic, railDisasterLedTo, changes in rail safety regulations in Canada]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railDisasterLedTo Context triple: [Lac-Mégantic, railDisasterLedTo, changes in rail safety regulations in Canada]
-
A.
railDisasterCasualties
Indicates the number of people killed or injured as a result of a specific rail disaster.
-
B.
railDisasterYear
Indicates the year in which a rail-related disaster occurred.
-
C.
deadliestRailAccidentInJapanSince
Indicates that a rail accident is the most lethal one in Japan occurring on or after a specified date or event.
-
D.
numberOfCarsDerailed
Indicates the count of cars that have come off the tracks in a derailment incident.
-
E.
tramwayDestroyedBy
Indicates that a tramway was damaged or rendered unusable as a direct result of an action or event caused by another entity.
- 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_69f0ef878574819088c867fd1a5c8b86 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f68048391c8190abe6580678f8a9ef |
completed | May 2, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69f67e40af9881908de3a4aa15f70a83 |
completed | May 2, 2026, 10:44 p.m. |
| PDg | Predicate description generation | batch_69f67f7e116c819099aec724e9ef3763 |
completed | May 2, 2026, 10:49 p.m. |
Created at: April 28, 2026, 8:43 p.m.