Triple

T34582542
Position Surface form Disambiguated ID Type / Status
Subject Clem Hoatley E887947 entity
Predicate setting P1957 FINISHED
Object American carnival
An American carnival is a traveling entertainment event featuring rides, games, food stalls, and sideshows that typically visits towns and cities across the United States.
 E2101989 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: American carnival | Statement: [Clem Hoatley, setting, American carnival]
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: American carnival
Triple: [Clem Hoatley, setting, American carnival]
Generated description
An American carnival is a traveling entertainment event featuring rides, games, food stalls, and sideshows that typically visits towns and cities across the United States.

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_69f349d25cbc8190869998de5915886b completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f720c4ac8c8190a90b3e3d82d8c10d completed May 3, 2026, 10:17 a.m.
NED1 Entity disambiguation (via context triple) batch_6a37363a801c8190a430e3b1cf5fa6d5 completed June 21, 2026, 12:54 a.m.
NEDg Description generation batch_6a37370bb7048190aac369ca087f626e completed June 21, 2026, 12:57 a.m.
NED2 Entity disambiguation (via description) batch_6a373797117881908e7547c3eae9fd9a completed June 21, 2026, 1 a.m.
Created at: May 1, 2026, 2:03 a.m.