Triple

T32900
Position Surface form Disambiguated ID Type / Status
Subject United States Reports E656 entity
Predicate includesNominativeReports P1393 FINISHED
Object Peters
Peters is a set of early United States Supreme Court case reports compiled by Richard Peters, later incorporated into the official United States Reports.
 E7028 NE FINISHED

How this triple was built (4 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: Peters | Statement: [United States Reports, includesNominativeReports, Peters]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Peters
Context triple: [United States Reports, includesNominativeReports, Peters]
  • A. Porter
    Porter is a transit station in Cambridge, Massachusetts that serves both MBTA commuter rail and Red Line subway services.
  • B. Theodor
    Theodor "Ted" Nelson is an American pioneer of information technology best known for coining the term "hypertext" and envisioning global hyperlinked document systems.
  • C. Herbert
    Herbert is a masculine given name of Germanic origin that has been borne by various notable figures, including U.S. President Herbert Hoover.
  • D. Pierre
    Pierre is a masculine given name of French origin that has been borne by numerous notable figures in history, arts, and science.
  • E. Edwin
    Edwin is a masculine given name of Old English origin meaning "rich friend" or "prosperous friend."
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Peters
Triple: [United States Reports, includesNominativeReports, Peters]
Generated description
Peters is a set of early United States Supreme Court case reports compiled by Richard Peters, later incorporated into the official United States Reports.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Peters
Target entity description: Peters is a set of early United States Supreme Court case reports compiled by Richard Peters, later incorporated into the official United States Reports.
  • A. Porter
    Porter is a transit station in Cambridge, Massachusetts that serves both MBTA commuter rail and Red Line subway services.
  • B. Theodor
    Theodor "Ted" Nelson is an American pioneer of information technology best known for coining the term "hypertext" and envisioning global hyperlinked document systems.
  • C. Herbert
    Herbert is a masculine given name of Germanic origin that has been borne by various notable figures, including U.S. President Herbert Hoover.
  • D. Pierre
    Pierre is a masculine given name of French origin that has been borne by numerous notable figures in history, arts, and science.
  • E. Edwin
    Edwin is a masculine given name of Old English origin meaning "rich friend" or "prosperous friend."
  • F. None of above. chosen

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_69a2479dec388190967ba648663442c9 completed Feb. 28, 2026, 1:40 a.m.
NER Named-entity recognition batch_69a24ac8d59c8190aaf6607f2792ba3a completed Feb. 28, 2026, 1:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69a25ab0fb1c8190a7e8f31bf4d56eaf completed Feb. 28, 2026, 3:02 a.m.
NEDg Description generation batch_69a25ce7c718819096a51f15d7c6acee completed Feb. 28, 2026, 3:11 a.m.
NED2 Entity disambiguation (via description) batch_69a25daa5c188190b95c031dd646b704 completed Feb. 28, 2026, 3:14 a.m.
Created at: Feb. 28, 2026, 1:44 a.m.