Triple
T35618907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shigaraki Kōgen Railway |
E1029253
|
entity |
| Predicate | ShigarakiTrainDisasterYear |
P145365
|
FINISHED |
| Object | 1991 |
—
|
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: 1991 | Statement: [Shigaraki Kōgen Railway, ShigarakiTrainDisasterYear, 1991]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ShigarakiTrainDisasterYear Context triple: [Shigaraki Kōgen Railway, ShigarakiTrainDisasterYear, 1991]
-
A.
deadliestRailAccidentInJapanSince
Indicates that a rail accident is the most lethal one in Japan occurring on or after a specified date or event.
-
B.
railDisasterYear
chosen
Indicates the year in which a rail-related disaster occurred.
-
C.
railDisasterLedTo
Indicates that a specific rail disaster resulted in, caused, or gave rise to a particular subsequent event, consequence, or outcome.
-
D.
JapaneseCasualtiesSurvivors
Indicates the number or status of Japanese individuals who were casualties but survived an event or conflict.
-
E.
railDisasterCasualties
Indicates the number of people killed or injured as a result of a specific rail disaster.
- 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_69f76e0709408190bbe322bf1707ef6b |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79eee67e88190b314fdf1124fee29 |
completed | May 3, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69f79e4bdbcc8190be7a0d2cf8a77b64 |
completed | May 3, 2026, 7:13 p.m. |
Created at: May 3, 2026, 4:05 p.m.