Triple

T1494948
Position Surface form Disambiguated ID Type / Status
Subject Holden Chapel E29664 entity
Predicate namedAfter P63 FINISHED
Object Samuel Holden
Samuel Holden was an influential 18th-century British politician and merchant whose prominence and philanthropy led to institutions such as Holden Chapel being named in his honor.
 E232604 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: Samuel Holden | Statement: [Holden Chapel, namedAfter, Samuel Holden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Samuel Holden
Context triple: [Holden Chapel, namedAfter, Samuel Holden]
  • A. Samuel Ellis
    Samuel Ellis was the landowner after whom Ellis Island in New York Harbor was named.
  • B. Samuel Barnes
    Samuel Barnes is an author known for his work with the Juicy brand.
  • C. Samuel Allison
    Samuel Allison was an American physicist known for his work on nuclear physics and his leadership role in the Manhattan Project at the University of Chicago’s Metallurgical Laboratory.
  • D. Samuel McIntire
    Samuel McIntire was an influential early American architect and woodcarver from Salem, Massachusetts, renowned for his Federal-style designs and decorative craftsmanship.
  • E. Samuel Blatchford
    Samuel Blatchford was an Associate Justice of the U.S. Supreme Court in the late 19th century, known for his expertise in admiralty and patent law.
  • 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: Samuel Holden
Triple: [Holden Chapel, namedAfter, Samuel Holden]
Generated description
Samuel Holden was an influential 18th-century British politician and merchant whose prominence and philanthropy led to institutions such as Holden Chapel being named in his honor.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Samuel Holden
Target entity description: Samuel Holden was an influential 18th-century British politician and merchant whose prominence and philanthropy led to institutions such as Holden Chapel being named in his honor.
  • A. Samuel Ellis
    Samuel Ellis was the landowner after whom Ellis Island in New York Harbor was named.
  • B. Samuel Barnes
    Samuel Barnes is an author known for his work with the Juicy brand.
  • C. Samuel Allison
    Samuel Allison was an American physicist known for his work on nuclear physics and his leadership role in the Manhattan Project at the University of Chicago’s Metallurgical Laboratory.
  • D. Samuel McIntire
    Samuel McIntire was an influential early American architect and woodcarver from Salem, Massachusetts, renowned for his Federal-style designs and decorative craftsmanship.
  • E. Samuel Blatchford
    Samuel Blatchford was an Associate Justice of the U.S. Supreme Court in the late 19th century, known for his expertise in admiralty and patent law.
  • 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_69a498dba1d8819093b46a3a8d2485f1 completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c6c78c9481909b210b845aa6e9df completed March 1, 2026, 11:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae26de62d48190849540112614ccce completed March 9, 2026, 1:48 a.m.
NEDg Description generation batch_69ae2763b4b08190b733e8342a52f75e completed March 9, 2026, 1:50 a.m.
NED2 Entity disambiguation (via description) batch_69ae27d10bf08190a14fa1ca906646f8 completed March 9, 2026, 1:52 a.m.
Created at: March 1, 2026, 8:12 p.m.