Triple

T2871120
Position Surface form Disambiguated ID Type / Status
Subject Bryan Harper E63562 entity
Predicate familyName P18 FINISHED
Object Harper
Harper is a common English surname borne by numerous notable individuals across fields such as politics, sports, literature, and entertainment.
 E37141 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: Harper | Statement: [Bryan Harper, familyName, Harper]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Harper
Context triple: [Bryan Harper, familyName, Harper]
  • A. Harper
    Harper is a major American publishing house known for releasing a wide range of influential fiction and nonfiction works.
  • B. Spencer
    Spencer is a small town in central Massachusetts known for its New England character and historic mill village roots.
  • C. Spencer
    Spencer is the middle name of American author and aviator Anne Spencer Lindbergh, reflecting her family’s naming tradition.
  • D. Spencer
    Spencer is a masculine given name of English origin, historically associated with roles such as steward or dispenser and borne by various notable figures.
  • E. Griffin
    The Griffin is the mythical lion-eagle creature that serves as the official mascot of the College of William & Mary, symbolizing the school’s blend of strength, wisdom, and historical heritage.
  • 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: Harper
Triple: [Bryan Harper, familyName, Harper]
Generated description
Harper is a common English surname borne by numerous notable individuals across fields such as politics, sports, literature, and entertainment.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Harper
Target entity description: Harper is a common English surname borne by numerous notable individuals across fields such as politics, sports, literature, and entertainment.
  • A. Harper chosen
    Harper is a major American publishing house known for releasing a wide range of influential fiction and nonfiction works.
  • B. Spencer
    Spencer is a small town in central Massachusetts known for its New England character and historic mill village roots.
  • C. Spencer
    Spencer is a masculine given name of English origin, historically associated with roles such as steward or dispenser and borne by various notable figures.
  • D. Spencer
    Spencer is the middle name of American author and aviator Anne Spencer Lindbergh, reflecting her family’s naming tradition.
  • E. Griffin
    The Griffin is the mythical lion-eagle creature that serves as the official mascot of the College of William & Mary, symbolizing the school’s blend of strength, wisdom, and historical heritage.
  • F. None of above.

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_69ab4c42fb8c8190b36e161d47c03b81 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdfe2dcb48190a194253e733d14af completed March 7, 2026, 8:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69b01db01d348190945ab982ce5c5b2d completed March 10, 2026, 1:33 p.m.
NEDg Description generation batch_69b0201470cc81909188573c3749dffb completed March 10, 2026, 1:43 p.m.
NED2 Entity disambiguation (via description) batch_69b020aa00888190a683a621f1e1a107 completed March 10, 2026, 1:46 p.m.
Created at: March 6, 2026, 10:02 p.m.