Triple
T9694773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bojinka plot |
E234619
|
entity |
| Predicate | numberOfIntendedAirliners |
P5710
|
FINISHED |
| Object | 11 |
—
|
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: 11 | Statement: [Bojinka plot, numberOfIntendedAirliners, 11]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfIntendedAirliners Context triple: [Bojinka plot, numberOfIntendedAirliners, 11]
-
A.
numberOfPlanes
chosen
Indicates the quantity of planes associated with or involved in a given entity or situation.
-
B.
intendedAircraft
Indicates that an aircraft is the one planned or designated to be used for a particular flight, mission, or operation.
-
C.
aircraftCapacity
Indicates the maximum number of passengers or amount of load that an aircraft is designed or allowed to carry.
-
D.
planeNumber
Indicates that an entity is associated with a specific airplane identification number (such as a tail number or flight number).
-
E.
numberOfFuselages
Indicates the quantity of fuselages associated with or contained in a given object or configuration.
- 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_69ca84cb580c8190a7e5f4b3bcdaf2a4 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9d348868819083aec7a5da8c455b |
completed | April 1, 2026, 10:33 p.m. |
| PD | Predicate disambiguation | batch_69ccd5b840f081909f66bf0b66d17d9b |
completed | April 1, 2026, 8:22 a.m. |
Created at: March 30, 2026, 8:17 p.m.