Triple

T38207117
Position Surface form Disambiguated ID Type / Status
Subject Claude Crozet E1009230 entity
Predicate workLocation P7 FINISHED
Object Virginia
Virginia is a U.S. state in the Mid-Atlantic and Southeastern regions, known for its pivotal role in American colonial history, the Revolutionary and Civil Wars, and as the home state of numerous early presidents.
E5410 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: Virginia | Statement: [Claude Crozet, workLocation, Virginia]
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: Virginia
Triple: [Claude Crozet, workLocation, Virginia]
Generated description
Virginia is a U.S. state in the Mid-Atlantic and Southeastern regions, known for its pivotal role in American colonial history, the Revolutionary and Civil Wars, and as the home state of numerous early presidents.

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_69f76dc94fcc8190bd2f55e81f9d6527 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69fcb131d0348190bd18f87ecc648afb completed May 7, 2026, 3:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4193bf54208190ba0ba2fc12b5abca completed June 28, 2026, 9:35 p.m.
NEDg Description generation batch_6a41947a2f608190aba9f20c7e4cd8d6 completed June 28, 2026, 9:39 p.m.
NED2 Entity disambiguation (via description) batch_6a4195210170819086828d7780a6e407 completed June 28, 2026, 9:41 p.m.
Created at: May 3, 2026, 4:30 p.m.