Triple
T30760731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Extraordinary African Chambers trial of Hissène Habré |
E783225
|
entity |
| Predicate | victimCountFinding |
P74879
|
FINISHED |
| Object | tens of thousands of victims |
—
|
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: tens of thousands of victims | Statement: [Extraordinary African Chambers trial of Hissène Habré, victimCountFinding, tens of thousands of victims]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: victimCountFinding Context triple: [Extraordinary African Chambers trial of Hissène Habré, victimCountFinding, tens of thousands of victims]
-
A.
victimCountPolicy
Indicates the rule or criterion used to determine how victims are counted or classified in a given context.
-
B.
numberOfVictimsClaimed
chosen
Indicates the reported count of victims associated with a particular event, incident, or action.
-
C.
victimOrder
Indicates the sequence or ranking of victims involved in an event or incident.
-
D.
numberOfSuspectedVictims
Indicates the count of individuals believed or alleged to be victims in a particular incident, case, or context.
-
E.
numberOfVictimsConfirmed
Indicates the confirmed count of victims associated with an event, incident, or situation.
- 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_69f224b047f48190b4f5efeb7ee97b37 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69dfdda708190be290c7bec205445 |
completed | May 3, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69f69d1a37e081908d1d86b90ff502bd |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 29, 2026, 8:39 p.m.