Triple

T31642516
Position Surface form Disambiguated ID Type / Status
Subject Registrar of the International Criminal Tribunal for Rwanda E807492 entity
Predicate firstHolder P291 FINISHED
Object André Guichaoua
André Guichaoua is a French sociologist and expert on Rwanda known for his extensive research and testimony on the Rwandan genocide and international justice.
E1971171 NE 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: André Guichaoua | Statement: [Registrar of the International Criminal Tribunal for Rwanda, firstHolder, André Guichaoua]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: André Guichaoua
Triple: [Registrar of the International Criminal Tribunal for Rwanda, firstHolder, André Guichaoua]
Generated description
André Guichaoua is a French sociologist and expert on Rwanda known for his extensive research and testimony on the Rwandan genocide and international justice.

Provenance (5 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_69f348d9ce58819093ea2da83cbeeec1 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a91c1d3c8190b7c11e5a75921aff completed May 3, 2026, 1:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b79dcdc188190aa89e3bbcf642048 completed June 12, 2026, 3:15 a.m.
NEDg Description generation batch_6a2b7b4089e08190900d25e60ae9aaa9 completed June 12, 2026, 3:21 a.m.
NED2 Entity disambiguation (via description) batch_6a2b7c947858819091eb97bfa084e5a9 completed June 12, 2026, 3:27 a.m.
Created at: April 30, 2026, 10:50 p.m.