Triple

T14311727
Position Surface form Disambiguated ID Type / Status
Subject Hanna v. Plumer E354848 entity
Predicate petitioner P3132 FINISHED
Object Hanna
Hanna is the petitioner in the U.S. Supreme Court case Hanna v. Plumer, which addressed the application of federal procedural rules in diversity jurisdiction cases.
 E1091403 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: Hanna | Statement: [Hanna v. Plumer, petitioner, Hanna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hanna
Context triple: [Hanna v. Plumer, petitioner, Hanna]
  • A. Hanna
    Hanna was the wife of the influential 16th-century Jewish legal scholar and codifier Rabbi Joseph Karo.
  • B. Hanna
    "Hanna" is a 2011 action thriller film about a teenage girl trained as an assassin, known for its stylized direction and electronic score by The Chemical Brothers.
  • C. Till
    Till is a character in Anzia Yezierska’s novel "Sapphira and the Slave Girl," contributing to the book’s exploration of race, power, and personal freedom in antebellum America.
  • D. Jejuri
    Jejuri is a temple town in Maharashtra, India, renowned for its hilltop Khandoba temple and vibrant religious festivals.
  • E. Annette
    Annette is a feminine given name of French origin, commonly used in various European and English-speaking countries.
  • 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: Hanna
Triple: [Hanna v. Plumer, petitioner, Hanna]
Generated description
Hanna is the petitioner in the U.S. Supreme Court case Hanna v. Plumer, which addressed the application of federal procedural rules in diversity jurisdiction cases.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hanna
Target entity description: Hanna is the petitioner in the U.S. Supreme Court case Hanna v. Plumer, which addressed the application of federal procedural rules in diversity jurisdiction cases.
  • A. Hanna
    Hanna was the wife of the influential 16th-century Jewish legal scholar and codifier Rabbi Joseph Karo.
  • B. Hanna
    "Hanna" is a 2011 action thriller film about a teenage girl trained as an assassin, known for its stylized direction and electronic score by The Chemical Brothers.
  • C. Till
    Till is a character in Anzia Yezierska’s novel "Sapphira and the Slave Girl," contributing to the book’s exploration of race, power, and personal freedom in antebellum America.
  • D. Jejuri
    Jejuri is a temple town in Maharashtra, India, renowned for its hilltop Khandoba temple and vibrant religious festivals.
  • E. Annette
    Annette is a feminine given name of French origin, commonly used in various European and English-speaking countries.
  • 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_69d8278ed42c8190b9f882dcce611347 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de85b386d0819087d14f3ce84a1997 completed April 14, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd3d3124488190b2ea35949294e297 completed May 8, 2026, 1:32 a.m.
NEDg Description generation batch_69fd3ded77748190b35908e046ccce67 completed May 8, 2026, 1:35 a.m.
NED2 Entity disambiguation (via description) batch_69fd3e7425348190abf09c103cc17305 completed May 8, 2026, 1:37 a.m.
Created at: April 10, 2026, 1:12 a.m.