Triple

T34201859
Position Surface form Disambiguated ID Type / Status
Subject International Center for Transitional Justice E877406 entity
Predicate foundedBy P104 FINISHED
Object Paul van Zyl
Paul van Zyl is a South African human rights lawyer and transitional justice expert known for co-founding and leading global efforts to address mass atrocities and support post-conflict reconciliation.
E2102685 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: Paul van Zyl | Statement: [International Center for Transitional Justice, foundedBy, Paul van Zyl]
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: Paul van Zyl
Triple: [International Center for Transitional Justice, foundedBy, Paul van Zyl]
Generated description
Paul van Zyl is a South African human rights lawyer and transitional justice expert known for co-founding and leading global efforts to address mass atrocities and support post-conflict reconciliation.

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_69f349aff5f0819096275315abea5344 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f7104bcc1c8190b99eed0d5b1faf90 completed May 3, 2026, 9:07 a.m.
NED1 Entity disambiguation (via context triple) batch_6a373606cbdc819082aa0b391887fde9 completed June 21, 2026, 12:53 a.m.
NEDg Description generation batch_6a37368f20cc8190890a915e66621f6d completed June 21, 2026, 12:55 a.m.
NED2 Entity disambiguation (via description) batch_6a373711fb94819086195281459bb17e completed June 21, 2026, 12:57 a.m.
Created at: May 1, 2026, 1:55 a.m.