Triple
T2053520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International Criminal Tribunal for Rwanda |
E45621
|
entity |
| Predicate | numberOfIndictedPersonsApproximate |
P35608
|
FINISHED |
| Object | 93 |
—
|
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: 93 | Statement: [International Criminal Tribunal for Rwanda, numberOfIndictedPersonsApproximate, 93]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfIndictedPersonsApproximate Context triple: [International Criminal Tribunal for Rwanda, numberOfIndictedPersonsApproximate, 93]
-
A.
numberOfPeopleAccused
Indicates the count of individuals who are formally alleged to have committed a particular act or offense.
-
B.
numberOfPrisonersApproximate
Indicates an approximate count of prisoners associated with an entity or situation, rather than an exact number.
-
C.
estimatedPrisonerCount
Indicates the estimated number of prisoners associated with a particular context, such as a location, time period, or event.
-
D.
estimatedPrisoners
Indicates a relationship where a value represents the estimated number of prisoners associated with a particular entity or context.
-
E.
numberOfArrests
Indicates the count of times an entity has been arrested.
- 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_69a8891a19508190a12ef1e192308dcb |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb99196ec819096f491ac7732156a |
completed | March 7, 2026, 5:37 a.m. |
| PD | Predicate disambiguation | batch_69abb7abba508190b872f345d3ba51bb |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb94ec400819097596732aabed854 |
completed | March 7, 2026, 5:36 a.m. |
Created at: March 4, 2026, 7:39 p.m.