Triple
T324871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | September 11 attacks |
E6490
|
entity |
| Predicate | numberOfHijackers |
P12811
|
FINISHED |
| Object | 19 |
—
|
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: 19 | Statement: [September 11 attacks, numberOfHijackers, 19]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfHijackers Context triple: [September 11 attacks, numberOfHijackers, 19]
-
A.
passengers
Indicates that one entity is traveling in or being transported by another entity, typically as a non-operating occupant.
-
B.
numberOfPlanes
Indicates the quantity of planes associated with or involved in a given entity or situation.
-
C.
numberOfInvaders
Indicates the quantity of entities classified as invaders associated with a given subject or context.
-
D.
passengersCountApproximate
Indicates that the number of passengers involved is given as an approximate or estimated count rather than an exact figure.
-
E.
numberOfPeopleAccused
Indicates the count of individuals who are formally alleged to have committed a particular act or offense.
- F. None of above. chosen
Provenance (4 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_69a2e7933d6c8190bb2592ad13286ef2 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eb1a37c08190b1380f6bf8513a37 |
completed | Feb. 28, 2026, 1:18 p.m. |
| PD | Predicate disambiguation | batch_69a2e949364c8190bc2351f5413f5057 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2eb18bda48190ac3d96a61a6a684d |
completed | Feb. 28, 2026, 1:18 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.