Triple

T26124104
Position Surface form Disambiguated ID Type / Status
Subject Nevada ghost towns E659053 entity
Predicate hasPart P35 FINISHED
Object Metropolis, Nevada
Metropolis, Nevada is an early 20th-century planned agricultural town in Elko County that was abandoned after irrigation failures and is now preserved as a notable ghost town.
E1836547 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: Metropolis, Nevada | Statement: [Nevada ghost towns, hasPart, Metropolis, Nevada]
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: Metropolis, Nevada
Triple: [Nevada ghost towns, hasPart, Metropolis, Nevada]
Generated description
Metropolis, Nevada is an early 20th-century planned agricultural town in Elko County that was abandoned after irrigation failures and is now preserved as a notable ghost town.

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_69ee5bc2b2948190b458ad3f580af779 completed April 26, 2026, 6:38 p.m.
NER Named-entity recognition batch_69f60acf9f5c819095cc60b81bea1b59 completed May 2, 2026, 2:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24bb731c0481909aa3925e209c2198 completed June 7, 2026, 12:29 a.m.
NEDg Description generation batch_6a24bfb0987c819089a6705bb5282c4e completed June 7, 2026, 12:47 a.m.
NED2 Entity disambiguation (via description) batch_6a24c54a5d648190b33935999d8f5f04 completed June 7, 2026, 1:11 a.m.
Created at: April 26, 2026, 8:10 p.m.