Triple
T29771876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lac-Mégantic |
E755269
|
entity |
| Predicate | railDisasterCasualties |
P168682
|
FINISHED |
| Object | 47 deaths |
—
|
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: 47 deaths | Statement: [Lac-Mégantic, railDisasterCasualties, 47 deaths]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railDisasterCasualties Context triple: [Lac-Mégantic, railDisasterCasualties, 47 deaths]
-
A.
railDisasterYear
Indicates the year in which a rail-related disaster occurred.
-
B.
causedFatalities
Indicates that the referenced event or action directly resulted in one or more deaths.
-
C.
primaryCasualtiesFrom
Indicates that an entity is the main source or cause of the casualties experienced by another entity.
-
D.
notableDeathTollEvent
Indicates that an event is characterized by causing an unusually large or historically significant number of deaths.
-
E.
constructionAccidentFatalities
Indicates that a construction-related accident resulted in one or more fatalities.
- 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_69f67595fa7c8190b6e9f7a8c700dd97 |
completed | May 2, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69f673c4abec8190bc2379e66f4af0a9 |
completed | May 2, 2026, 9:59 p.m. |
| PDg | Predicate description generation | batch_69f674df80b08190adb7f7531083bbb1 |
completed | May 2, 2026, 10:04 p.m. |
Created at: April 28, 2026, 8:43 p.m.