Triple
T1951555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Airlines Flight 11 |
E42168
|
entity |
| Predicate | fatalitiesOnboard |
P33471
|
FINISHED |
| Object | 92 |
—
|
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: 92 | Statement: [American Airlines Flight 11, fatalitiesOnboard, 92]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fatalitiesOnboard Context triple: [American Airlines Flight 11, fatalitiesOnboard, 92]
-
A.
crewFatality
Indicates that one or more members of a crew have died as a result of the related event or situation.
-
B.
fatalitiesCategory
Indicates the classification of deaths associated with an event, incident, or condition into a specific category or severity level.
-
C.
casualties
Indicates that an event, action, or situation resulted in people being killed or injured.
-
D.
diedOnJourneyBetween
Indicates that an entity died while traveling between two specified locations or points in a journey.
-
E.
aircraftInvolvedInDeath
Indicates that an aircraft played a direct role in causing or contributing to a person's death.
- 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_69a8870e08fc8190a319cbf2600db15f |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb34eb5748190a3ac395252951eba |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abaff3eda88190b643994cb4dfb8df |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb1ddccbc8190bf2bd8bac673c0c5 |
completed | March 7, 2026, 5:04 a.m. |
Created at: March 4, 2026, 7:36 p.m.