Triple
T18446204
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dawson's Field hijackings |
E450664
|
entity |
| Predicate | numberOfAircraftHijacked |
P5710
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Dawson's Field hijackings, numberOfAircraftHijacked, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfAircraftHijacked Context triple: [Dawson's Field hijackings, numberOfAircraftHijacked, 4]
-
A.
numberOfHijackers
Indicates the quantity of individuals who carried out or attempted to carry out a hijacking in the described event or context.
-
B.
casualtiesHijackers
Indicates that the hijackers caused or were responsible for casualties (deaths or injuries) among others.
-
C.
numberOfHostages
Indicates the quantity of hostages involved in a particular situation, event, or context.
-
D.
hijacked
Indicates that one entity has forcibly taken control of another entity, typically without authorization and against the will of its rightful controller.
-
E.
numberOfPlanes
chosen
Indicates the quantity of planes associated with or involved in a given entity or situation.
- 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_69d8d38345688190b565eac2e4cd7935 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e52644959c8190b1117608e5fa15aa |
completed | April 19, 2026, 7 p.m. |
| PD | Predicate disambiguation | batch_69e469c943a4819094c8fdc5971ad3a7 |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:30 a.m.