Triple

T28659975
Position Surface form Disambiguated ID Type / Status
Subject Sidney Abrahams E725437 entity
Predicate positionHeld P8 FINISHED
Object Chief Justice of Palestine
The Chief Justice of Palestine was the highest-ranking judicial officer in the British Mandate of Palestine, overseeing the administration and supervision of the territory’s court system.
E1827510 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: Chief Justice of Palestine | Statement: [Sidney Abrahams, positionHeld, Chief Justice of Palestine]
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: Chief Justice of Palestine
Triple: [Sidney Abrahams, positionHeld, Chief Justice of Palestine]
Generated description
The Chief Justice of Palestine was the highest-ranking judicial officer in the British Mandate of Palestine, overseeing the administration and supervision of the territory’s court system.

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_69f01d84f5f0819087ab5e6143b14ed7 completed April 28, 2026, 2:37 a.m.
NER Named-entity recognition batch_69f6559f097c81908e32fad12d99ae3a completed May 2, 2026, 7:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cc39016e48190b7c5230b1d367c1c completed May 31, 2026, 11:26 p.m.
NEDg Description generation batch_6a1cc44b6ac081909cd782a2b589b6f5 completed May 31, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_6a1cc547f02c81909061621839dd4e6e completed May 31, 2026, 11:33 p.m.
Created at: April 28, 2026, 4:57 a.m.