Triple

T36481871
Position Surface form Disambiguated ID Type / Status
Subject USCM Annual Meeting E898836 entity
Predicate relatedEvent P37 FINISHED
Object USCM Winter Meeting
The USCM Winter Meeting is a seasonal gathering of U.S. mayors organized by the United States Conference of Mayors to discuss urban policy, federal-city relations, and municipal priorities.
 E2186554 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: USCM Winter Meeting | Statement: [USCM Annual Meeting, relatedEvent, USCM Winter Meeting]
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: USCM Winter Meeting
Triple: [USCM Annual Meeting, relatedEvent, USCM Winter Meeting]
Generated description
The USCM Winter Meeting is a seasonal gathering of U.S. mayors organized by the United States Conference of Mayors to discuss urban policy, federal-city relations, and municipal priorities.

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_69f76e5a0e088190a2b6706aeb41723c completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bdfe8f348190a5592f04298a79b3 completed May 3, 2026, 9:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39cfdcfd2881908ddd007bb6f94a80 completed June 23, 2026, 12:14 a.m.
NEDg Description generation batch_6a39d15608a0819080084bf7b4a48f4a completed June 23, 2026, 12:20 a.m.
NED2 Entity disambiguation (via description) batch_6a39d25c790081909b49e0f4d4f29861 completed June 23, 2026, 12:25 a.m.
Created at: May 3, 2026, 4:10 p.m.