Triple
T1951531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Airlines Flight 11 |
E42168
|
entity |
| Predicate | hijackersCount |
P12811
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [American Airlines Flight 11, hijackersCount, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hijackersCount Context triple: [American Airlines Flight 11, hijackersCount, 5]
-
A.
numberOfHijackers
chosen
Indicates the quantity of individuals who carried out or attempted to carry out a hijacking in the described event or context.
-
B.
crewCount
Indicates the number of crew members associated with an entity, such as a vehicle, vessel, or mission.
-
C.
passengers
Indicates that one entity is traveling in or being transported by another entity, typically as a non-operating occupant.
-
D.
crewCountApproximate
Indicates that the relationship specifies an estimated or approximate number of crew members associated with an entity.
-
E.
passengerCount
Indicates the number of passengers associated with a given entity, such as a vehicle or trip.
- 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_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. |
Created at: March 4, 2026, 7:36 p.m.