Triple

T36836540
Position Surface form Disambiguated ID Type / Status
Subject Partnership2Gether E910286 entity
Predicate alternativeName P39 FINISHED
Object Partnership 2000
Partnership 2000 is a Jewish Agency initiative that builds and strengthens long-term, people-to-people relationships between Israeli communities and Jewish communities around the world.
E2200261 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: Partnership 2000 | Statement: [Partnership2Gether, alternativeName, Partnership 2000]
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: Partnership 2000
Triple: [Partnership2Gether, alternativeName, Partnership 2000]
Generated description
Partnership 2000 is a Jewish Agency initiative that builds and strengthens long-term, people-to-people relationships between Israeli communities and Jewish communities around the world.

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_69f76e7e9d60819092442fba73290a46 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7cf7e03d48190a98fd489ef0bccaf completed May 3, 2026, 10:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3dde722de8819088707a69406c30c9 completed June 26, 2026, 2:05 a.m.
NEDg Description generation batch_6a3de007551c8190987f689f90968eed completed June 26, 2026, 2:12 a.m.
NED2 Entity disambiguation (via description) batch_6a3de48f5cc48190b6ede4caf8298853 completed June 26, 2026, 2:31 a.m.
Created at: May 3, 2026, 4:13 p.m.