Triple
T27502389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abbeystead Dam |
E694192
|
entity |
| Predicate | casualtiesInIncident |
P35438
|
FINISHED |
| Object | 16 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: 16 deaths | Statement: [Abbeystead Dam, casualtiesInIncident, 16 deaths]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: casualtiesInIncident Context triple: [Abbeystead Dam, casualtiesInIncident, 16 deaths]
-
A.
casualties
Indicates that an event, action, or situation resulted in people being killed or injured.
-
B.
primaryCasualtiesFrom
Indicates that an entity is the main source or cause of the casualties experienced by another entity.
-
C.
casualtiesAssociatedWithEvent
chosen
Indicates that certain casualties (deaths or injuries) are linked to, or resulted from, a specific event.
-
D.
casualtiesDescription
Indicates a textual description of the human losses (such as deaths, injuries, or missing persons) resulting from an event or incident.
-
E.
casualtiesIncluded
Indicates that the referenced count or report of casualties explicitly includes the specified individuals or groups.
- 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_69ef538370888190b1ddf53bb4831188 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69f63fd6c68481908c542aa03e297b9c |
completed | May 2, 2026, 6:17 p.m. |
| PD | Predicate disambiguation | batch_69f63c663be481908f233d25d28713a4 |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 27, 2026, 1:11 p.m.