Triple
T2110021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khalid Sheikh Mohammed |
E42479
|
entity |
| Predicate | waterboardedTimes |
P34822
|
FINISHED |
| Object | 183 |
—
|
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: 183 | Statement: [Khalid Sheikh Mohammed, waterboardedTimes, 183]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterboardedTimes Context triple: [Khalid Sheikh Mohammed, waterboardedTimes, 183]
-
A.
hasBeenImprisonedBy
Indicates that one entity has been confined or incarcerated under the authority or control of another entity.
-
B.
wereInternedBy
Indicates that an entity was forcibly confined, detained, or held in an internment facility by another entity (typically an authority or government).
-
C.
servedPrisonTime
Indicates that an entity has spent a period of time incarcerated in prison as a consequence of a legal sentence.
-
D.
numberOfArrests
Indicates the count of times an entity has been arrested.
-
E.
numberSentencedToLifeImprisonment
Indicates the number of individuals who have been given a sentence of life imprisonment as a legal punishment.
- 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_69a8871040f08190aac2e2d0ab6b47ad |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbae1bacc8190beffc9d0470e9190 |
completed | March 7, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_69abb7ba08948190a3c236bb53ee4257 |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb85fe7a08190b991b1f23bc34f93 |
completed | March 7, 2026, 5:32 a.m. |
Created at: March 4, 2026, 7:43 p.m.