Triple

T11151331
Position Surface form Disambiguated ID Type / Status
Subject Arliss Howard E263792 entity
Predicate familyName P18 FINISHED
Object Howard
Howard is a common English surname borne by numerous notable figures across politics, entertainment, sports, and other fields.
E118997 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: Howard | Statement: [Arliss Howard, familyName, Howard]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Howard
Context triple: [Arliss Howard, familyName, Howard]
  • A. Howard
    Howard is the middle name of Edwin H. Armstrong, the pioneering American electrical engineer and inventor of FM radio.
  • B. Howard
    Howard is a volume series of early U.S. Supreme Court case reports compiled by Benjamin Chew Howard, later incorporated into the official United States Reports.
  • C. Howard
    Howard is a major Chicago Transit Authority rail station that serves as a key northern terminal and transfer point for multiple 'L' lines.
  • D. Howard
    Howard is the given first name of Ward Cunningham, the American computer programmer best known for creating the first wiki.
  • E. Howard
    Howard is a seasoned, wise old prospector in the classic 1948 film "The Treasure of the Sierra Madre," known for his experience, moral insight, and pivotal role in the gold-hunting expedition.
  • 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: Howard
Triple: [Arliss Howard, familyName, Howard]
Generated description
Howard is a common English surname borne by numerous notable figures across politics, entertainment, sports, and other fields.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Howard
Target entity description: Howard is a common English surname borne by numerous notable figures across politics, entertainment, sports, and other fields.
  • A. Howard chosen
    Howard is a common English surname shared by numerous notable figures across entertainment, politics, and other fields.
  • B. Howard
    Howard is a masculine given name of Old English origin meaning "high guardian" or "noble watchman," borne by numerous notable figures across politics, arts, and academia.
  • C. Howard
    Howard is the given name of the influential American film director, producer, and screenwriter Howard Hawks.
  • D. Howard
    Howard is the middle name of William Howard Taft, the 27th president of the United States and later Chief Justice of the Supreme Court.
  • E. Howard
    Howard is the middle name of Edwin H. Armstrong, the pioneering American electrical engineer and inventor of FM radio.
  • 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_69d6aa9ccddc8190868998c8b7beb060 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8719e74819095413abc6c79296c completed April 9, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4422ca62c81909a3a935fb7e28c34 completed April 19, 2026, 2:47 a.m.
NEDg Description generation batch_69e44c0a9edc8190a184244ba63f1c8f completed April 19, 2026, 3:29 a.m.
NED2 Entity disambiguation (via description) batch_69e4513731fc8190be0bae62d1e16e6f completed April 19, 2026, 3:51 a.m.
Created at: April 8, 2026, 9:28 p.m.