Triple

T33508201
Position Surface form Disambiguated ID Type / Status
Subject Mattress Factory Museum E858169 entity
Predicate hasNotableArtistExhibited P87461 FINISHED
Object Greer Lankton
Greer Lankton was an American artist known for her haunting, life-sized dolls and installations that explored gender, identity, and the body within the East Village art scene of the 1980s and 1990s.
E2053077 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: Greer Lankton | Statement: [Mattress Factory Museum, hasNotableArtistExhibited, Greer Lankton]
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: Greer Lankton
Triple: [Mattress Factory Museum, hasNotableArtistExhibited, Greer Lankton]
Generated description
Greer Lankton was an American artist known for her haunting, life-sized dolls and installations that explored gender, identity, and the body within the East Village art scene of the 1980s and 1990s.

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_69f3497721848190978fbee5e0a526f8 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6f669974081909159fbe1841c01bc completed May 3, 2026, 7:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3595c940188190a76b19f00cc5364d completed June 19, 2026, 7:17 p.m.
NEDg Description generation batch_6a359724ebd48190b7158f852f890b86 completed June 19, 2026, 7:23 p.m.
NED2 Entity disambiguation (via description) batch_6a3598177b708190ab4da13476634995 completed June 19, 2026, 7:27 p.m.
Created at: May 1, 2026, 1:38 a.m.