Triple

T496736
Position Surface form Disambiguated ID Type / Status
Subject Tobias Read E10309 entity
Predicate familyName P18 FINISHED
Object Read
Read is a surname shared by various notable individuals across fields such as politics, arts, and academia.
E61799 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: Read | Statement: [Tobias Read, familyName, Read]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Read
Context triple: [Tobias Read, familyName, Read]
  • A. Reading
    Reading is a major town in Berkshire, England, known as a key commercial and transport hub in the Thames Valley.
  • B. Woman Reading
    Woman Reading is a painting by French artist Henri Matisse that exemplifies his use of bold color and simplified forms to depict an intimate, contemplative interior scene.
  • C. La Lecture
    La Lecture is an early 20th-century painting by Pablo Picasso that depicts a contemplative female figure and reflects his evolving style during his transition from Cubism toward a more classical, figurative approach.
  • D. RE
    RE is the common abbreviation for the British Army’s Corps of Royal Engineers, responsible for military engineering and technical support.
  • E. Reedus
    Reedus is the surname of American actor and model Norman Reedus, best known for his role as Daryl Dixon on the television series "The Walking Dead."
  • 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: Read
Triple: [Tobias Read, familyName, Read]
Generated description
Read is a surname shared by various notable individuals across fields such as politics, arts, and academia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Read
Target entity description: Read is a surname shared by various notable individuals across fields such as politics, arts, and academia.
  • A. Reading
    Reading is a major town in Berkshire, England, known as a key commercial and transport hub in the Thames Valley.
  • B. Woman Reading
    Woman Reading is a painting by French artist Henri Matisse that exemplifies his use of bold color and simplified forms to depict an intimate, contemplative interior scene.
  • C. La Lecture
    La Lecture is an early 20th-century painting by Pablo Picasso that depicts a contemplative female figure and reflects his evolving style during his transition from Cubism toward a more classical, figurative approach.
  • D. RE
    RE is the common abbreviation for the British Army’s Corps of Royal Engineers, responsible for military engineering and technical support.
  • E. Reedus
    Reedus is the surname of American actor and model Norman Reedus, best known for his role as Daryl Dixon on the television series "The Walking Dead."
  • 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_69a2e847df8481909239ec08ccf1e376 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f116f1b4819082f88d6c747368ae completed Feb. 28, 2026, 1:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69a47d2f3a148190b1d81f0836063171 completed March 1, 2026, 5:53 p.m.
NEDg Description generation batch_69a47eb3d90c81908e633300c0c8011b completed March 1, 2026, 6 p.m.
NED2 Entity disambiguation (via description) batch_69a47f71e9408190b82f277bb74c2a13 completed March 1, 2026, 6:03 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.