Triple
T29771877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lac-Mégantic |
E755269
|
entity |
| Predicate | railDisasterImpactArea |
P76614
|
FINISHED |
| Object | downtown Lac-Mégantic |
—
|
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: downtown Lac-Mégantic | Statement: [Lac-Mégantic, railDisasterImpactArea, downtown Lac-Mégantic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railDisasterImpactArea Context triple: [Lac-Mégantic, railDisasterImpactArea, downtown Lac-Mégantic]
-
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.
trainStationAffected
Indicates that a train station is impacted or influenced by a particular event, condition, or action.
-
D.
disasterLocation
chosen
Indicates the place where a disaster occurs or has its primary impact.
-
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_69f676f968d08190a4adba0439b438c9 |
completed | May 2, 2026, 10:13 p.m. |
| PD | Predicate disambiguation | batch_69f675ff62c48190a634bbb8896973b9 |
completed | May 2, 2026, 10:09 p.m. |
Created at: April 28, 2026, 8:43 p.m.