Triple
T30869115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Satam Muhammed Abd al-Rahman al-Suqami |
E786285
|
entity |
| Predicate | wasOnFlight |
P164299
|
FINISHED |
| Object | American Airlines Flight 11 |
—
|
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: American Airlines Flight 11 | Statement: [Satam Muhammed Abd al-Rahman al-Suqami, wasOnFlight, American Airlines Flight 11]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasOnFlight Context triple: [Satam Muhammed Abd al-Rahman al-Suqami, wasOnFlight, American Airlines Flight 11]
-
A.
isFlownOn
Indicates that an entity (such as a person or object) travels or is transported using a particular aircraft or airline as the means of flight.
-
B.
hasFlownIn
chosen
Indicates that an entity has previously traveled by flying in or on another entity (such as an aircraft or similar vehicle).
-
C.
isFlownWith
Indicates that one entity travels by air together with, or using the same flight as, another entity.
-
D.
performedFlightTo
Indicates that an entity (such as an aircraft or airline) carried out a flight whose destination was a specified location.
-
E.
usedForPassengerFlights
Indicates that something serves as a means or facility for transporting passengers on flights.
- 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.