Triple
T30869131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Satam Muhammed Abd al-Rahman al-Suqami |
E786285
|
entity |
| Predicate | coHijackerOnFlight |
P87282
|
FINISHED |
| Object | Mohamed Atta |
—
|
NE NERFINISHED |
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: Mohamed Atta | Statement: [Satam Muhammed Abd al-Rahman al-Suqami, coHijackerOnFlight, Mohamed Atta]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coHijackerOnFlight Context triple: [Satam Muhammed Abd al-Rahman al-Suqami, coHijackerOnFlight, Mohamed Atta]
-
A.
coHijackerWith
chosen
Indicates that two or more individuals participated together in the act of hijacking the same target (e.g., vehicle, aircraft, or vessel).
-
B.
pilotHijacker
Indicates that the subject is a pilot who hijacks, or has hijacked, an aircraft.
-
C.
numberOfHijackers
Indicates the quantity of individuals who carried out or attempted to carry out a hijacking in the described 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.
stopoverAirportOfHijackedFlight
Indicates that an airport served as an intermediate stopover point for a flight that was hijacked.
- 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_69f224b9df2c819086f55f8bcf7f382e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f691cfeaa881908939a30f971ceec0 |
completed | May 3, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69f68b7d2794819092fef8a63f4f3de8 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 29, 2026, 8:47 p.m.