Triple

T33055376
Position Surface form Disambiguated ID Type / Status
Subject SIPA E845830 entity
Predicate hasUnit P35 FINISHED
Object Center for International Conflict Resolution
The Center for International Conflict Resolution is a research and practice institute at Columbia University's School of International and Public Affairs focused on understanding, preventing, and resolving violent conflicts worldwide.
E2034531 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: Center for International Conflict Resolution | Statement: [SIPA, hasUnit, Center for International Conflict Resolution]
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: Center for International Conflict Resolution
Triple: [SIPA, hasUnit, Center for International Conflict Resolution]
Generated description
The Center for International Conflict Resolution is a research and practice institute at Columbia University's School of International and Public Affairs focused on understanding, preventing, and resolving violent conflicts worldwide.

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_69f3495333b8819095e9af56855b9061 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d34386c48190b8d66e5ef199ed02 completed May 3, 2026, 4:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34e52017888190a06f560565dfeb45 completed June 19, 2026, 6:43 a.m.
NEDg Description generation batch_6a34e5f9f52c8190920d2db26c801c7f completed June 19, 2026, 6:47 a.m.
NED2 Entity disambiguation (via description) batch_6a34e82ab0b48190b73217391c4e9d64 completed June 19, 2026, 6:56 a.m.
Created at: May 1, 2026, 1:25 a.m.