Triple

T1428708
Position Surface form Disambiguated ID Type / Status
Subject Harold Davenport E30393 entity
Predicate familyName P18 FINISHED
Object Davenport
Davenport is an English surname of Norman origin that has been borne by various notable figures in mathematics, politics, and the arts.
E163259 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: Davenport | Statement: [Harold Davenport, familyName, Davenport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Davenport
Context triple: [Harold Davenport, familyName, Davenport]
  • A. Davenport, Iowa
    Davenport, Iowa is a major city along the Mississippi River in eastern Iowa, known as part of the Quad Cities metropolitan area and a regional hub for commerce and culture.
  • B. Cedar Rapids
    Cedar Rapids is a 2011 American comedy film starring Ed Helms as a naive insurance agent navigating unexpected misadventures at a regional conference in Iowa.
  • C. Dubuque
    Dubuque is a historic river city in northeastern Iowa known for its role as a regional economic and cultural hub along the Mississippi River.
  • D. Delano
    Delano is the middle name of Franklin D. Roosevelt, the 32nd president of the United States.
  • E. Delano
    Delano is a small agricultural city in California’s Central Valley known for its table grape production and historic role in the farm labor movement.
  • 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: Davenport
Triple: [Harold Davenport, familyName, Davenport]
Generated description
Davenport is an English surname of Norman origin that has been borne by various notable figures in mathematics, politics, and the arts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Davenport
Target entity description: Davenport is an English surname of Norman origin that has been borne by various notable figures in mathematics, politics, and the arts.
  • A. Davenport, Iowa
    Davenport, Iowa is a major city along the Mississippi River in eastern Iowa, known as part of the Quad Cities metropolitan area and a regional hub for commerce and culture.
  • B. Cedar Rapids
    Cedar Rapids is a 2011 American comedy film starring Ed Helms as a naive insurance agent navigating unexpected misadventures at a regional conference in Iowa.
  • C. Dubuque
    Dubuque is a historic river city in northeastern Iowa known for its role as a regional economic and cultural hub along the Mississippi River.
  • D. Delano
    Delano is the middle name of Franklin D. Roosevelt, the 32nd president of the United States.
  • E. Delano
    Delano is a small agricultural city in California’s Central Valley known for its table grape production and historic role in the farm labor movement.
  • 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_69a498fb823c8190a67ce4c4837e641a completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c4d9575881908bb58598e5a80590 completed March 1, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad016930ec8190ab3900d6f40c4aa0 completed March 8, 2026, 4:56 a.m.
NEDg Description generation batch_69ad01d1c01c81908917c4837ed2b393 completed March 8, 2026, 4:57 a.m.
NED2 Entity disambiguation (via description) batch_69ad0265f610819085a2dd293abd4812 completed March 8, 2026, 5 a.m.
Created at: March 1, 2026, 8 p.m.