Triple

T28399441
Position Surface form Disambiguated ID Type / Status
Subject General Assembly of ICCROM E719362 entity
Predicate hasAuthorityOver P544 FINISHED
Object ICCROM Council
The ICCROM Council is the governing body that oversees and guides the strategic direction and policies of ICCROM between sessions of its General Assembly.
E1825331 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: ICCROM Council | Statement: [General Assembly of ICCROM, hasAuthorityOver, ICCROM Council]
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: ICCROM Council
Triple: [General Assembly of ICCROM, hasAuthorityOver, ICCROM Council]
Generated description
The ICCROM Council is the governing body that oversees and guides the strategic direction and policies of ICCROM between sessions of its General Assembly.

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_69eff6efd1b08190ae3cefd4f11388a2 completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f64d68d2e4819080efa24d9e787303 completed May 2, 2026, 7:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cb6cf65d0819088e24fb0993bbcd0 completed May 31, 2026, 10:31 p.m.
NEDg Description generation batch_6a1cba824efc819080e74d94c5cc364e completed May 31, 2026, 10:47 p.m.
NED2 Entity disambiguation (via description) batch_6a1cbb3136f48190a03ed9dda2b55bbc completed May 31, 2026, 10:50 p.m.
Created at: April 28, 2026, 1:19 a.m.