Triple

T26575201
Position Surface form Disambiguated ID Type / Status
Subject Kenneth A. Roberts E666928 entity
Predicate familyName P18 FINISHED
Object Roberts
Roberts is a common English-language surname borne by numerous notable individuals across politics, arts, sports, and other fields.
E938305 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: Roberts | Statement: [Kenneth A. Roberts, familyName, Roberts]
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: Roberts
Triple: [Kenneth A. Roberts, familyName, Roberts]
Generated description
Roberts is a common English-language surname borne by numerous notable individuals across politics, arts, sports, and other fields.

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_69ee9cfa21c081909e4e36e087debfc6 completed April 26, 2026, 11:17 p.m.
NER Named-entity recognition batch_69f614dc21a08190bdc0e29beccadc43 completed May 2, 2026, 3:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11c82efa0081909d3b58f0d7861821 completed May 23, 2026, 3:30 p.m.
NEDg Description generation batch_6a11ca8102f08190b5e4ce3415151fd8 completed May 23, 2026, 3:40 p.m.
NED2 Entity disambiguation (via description) batch_6a11cb036a908190a43c3aee7dd4e0d6 completed May 23, 2026, 3:42 p.m.
Created at: April 27, 2026, 2 a.m.