Triple
T13484230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harrow & Wealdstone |
E318451
|
entity |
| Predicate | railAccidentYear |
P43898
|
FINISHED |
| Object | 1952 |
—
|
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: 1952 | Statement: [Harrow & Wealdstone, railAccidentYear, 1952]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railAccidentYear Context triple: [Harrow & Wealdstone, railAccidentYear, 1952]
-
A.
notableAccidentYear
chosen
Indicates the year in which a notable accident involving the subject occurred.
-
B.
aircraftAccidentYear
Indicates the calendar year in which an aircraft accident occurred.
-
C.
numberOfFatalAccidents
Indicates the total count of accidents within a given context that resulted in at least one fatality.
-
D.
accidentType
Indicates the specific category or kind of accident associated with an event or incident.
-
E.
deadliestRailAccidentInJapanSince
Indicates that a rail accident is the most lethal one in Japan occurring on or after a specified date or event.
- 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_69d806b6bfec819089222715b2e86c8e |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf3868ec8190a6a1803018d4f2d8 |
completed | April 12, 2026, 2:42 p.m. |
| PD | Predicate disambiguation | batch_69dbae06061881909a6a6032e0507587 |
completed | April 12, 2026, 2:36 p.m. |
Created at: April 9, 2026, 9:42 p.m.