Triple

T26851950
Position Surface form Disambiguated ID Type / Status
Subject Edward Terry Sanford E676080 entity
Predicate familyName P18 FINISHED
Object Sanford
Sanford is a surname most notably associated with Edward Terry Sanford, an American jurist who served as an Associate Justice of the U.S. Supreme Court in the early 20th century.
E1747695 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: Sanford | Statement: [Edward Terry Sanford, familyName, Sanford]
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: Sanford
Triple: [Edward Terry Sanford, familyName, Sanford]
Generated description
Sanford is a surname most notably associated with Edward Terry Sanford, an American jurist who served as an Associate Justice of the U.S. Supreme Court in the early 20th century.

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_69eee9b9d7708190a15d7485709ae981 completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f61b924d0c819089d6f99cc09bbe59 completed May 2, 2026, 3:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a121e76ce4c8190a223b8680691fc00 completed May 23, 2026, 9:39 p.m.
NEDg Description generation batch_6a121fa58ae08190b70faa7e3c81eae8 completed May 23, 2026, 9:44 p.m.
NED2 Entity disambiguation (via description) batch_6a12203ee42c8190be6d4c4d9f0ec859 completed May 23, 2026, 9:46 p.m.
Created at: April 27, 2026, 5:17 a.m.