Triple
T8246500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | demon core |
E192861
|
entity |
| Predicate | numberOfFatalAccidents |
P81159
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [demon core, numberOfFatalAccidents, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfFatalAccidents Context triple: [demon core, numberOfFatalAccidents, 2]
-
A.
constructionAccidentFatalities
Indicates that a construction-related accident resulted in one or more fatalities.
-
B.
fatalitiesCategory
Indicates the classification of deaths associated with an event, incident, or condition into a specific category or severity level.
-
C.
resultOfAccident
Indicates that something exists or occurs as a consequence or outcome of an accident.
-
D.
notableAccidentYear
Indicates the year in which a notable accident involving the subject occurred.
-
E.
numberOfPeopleLaterDyingOfInjuriesConsidered
Indicates the number of people who subsequently died from injuries that were previously evaluated or taken into account.
- 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_69ca82de7b8c81908d8106f8a53cff9b |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb787414508190a08cf47d1545ce50 |
completed | March 31, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69cb36b437e881909958591357e83b9d |
completed | March 31, 2026, 2:51 a.m. |
| PDg | Predicate description generation | batch_69cb447c146081909decf97bbd26c496 |
completed | March 31, 2026, 3:50 a.m. |
Created at: March 30, 2026, 5:48 p.m.