Triple
T36296293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wail Mohammed al-Shehri |
E893376
|
entity |
| Predicate | boardedFlightFrom |
P1521
|
FINISHED |
| Object | Logan International Airport, Boston |
—
|
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: Logan International Airport, Boston | Statement: [Wail Mohammed al-Shehri, boardedFlightFrom, Logan International Airport, Boston]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: boardedFlightFrom Context triple: [Wail Mohammed al-Shehri, boardedFlightFrom, Logan International Airport, Boston]
-
A.
originatingFlight
Indicates that one entity is the original or initial flight from which another flight, journey, or related record derives or is associated.
-
B.
hasOriginAirport
Indicates that something, typically a flight or journey, departs from or is associated with a specific origin airport.
-
C.
passengerFlight
Indicates a relationship where a flight is specifically operated to transport passengers rather than cargo or other purposes.
-
D.
destinationOfFlight
Indicates the location or place to which a given flight is traveling or scheduled to arrive.
-
E.
placeOfDeparture
chosen
Indicates the location from which an entity, such as a person or vehicle, begins its journey or movement.
- 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_69f76e4a61f0819084a2b68dbbb4efc6 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7ba6d06f48190a71b5a2f19e2232f |
completed | May 3, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a4aad48190a62e41c5e39339d9 |
completed | May 3, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:09 p.m.