Triple

T12633518
Position Surface form Disambiguated ID Type / Status
Subject Ordinatio E301701 entity
Predicate isRevisionOf P15288 FINISHED
Object Lectura
Lectura is an earlier version of John Duns Scotus’s theological commentary on Peter Lombard’s Sentences, preceding and later revised into the more polished Ordinatio.
 E998163 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: Lectura | Statement: [Ordinatio, isRevisionOf, Lectura]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lectura
Context triple: [Ordinatio, isRevisionOf, Lectura]
  • A. Reading
    Reading is a historic city in southeastern Pennsylvania known for its industrial heritage, transportation links, and role as a regional cultural and economic center.
  • B. Reading
    Reading is a major town in Berkshire, England, known as a key commercial and transport hub in the Thames Valley.
  • C. Reading
    "Reading" is an Impressionist painting by Berthe Morisot that depicts a quiet, intimate moment of a woman absorbed in a book.
  • D. Read
    Read is a surname shared by various notable individuals across fields such as politics, arts, and academia.
  • E. Read
    Read is a village in Lancashire, England, situated near the River Calder and known for its residential community and local amenities.
  • 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: Lectura
Triple: [Ordinatio, isRevisionOf, Lectura]
Generated description
Lectura is an earlier version of John Duns Scotus’s theological commentary on Peter Lombard’s Sentences, preceding and later revised into the more polished Ordinatio.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lectura
Target entity description: Lectura is an earlier version of John Duns Scotus’s theological commentary on Peter Lombard’s Sentences, preceding and later revised into the more polished Ordinatio.
  • A. Reading
    Reading is a historic city in southeastern Pennsylvania known for its industrial heritage, transportation links, and role as a regional cultural and economic center.
  • B. Reading
    Reading is a major town in Berkshire, England, known as a key commercial and transport hub in the Thames Valley.
  • C. Reading
    "Reading" is an Impressionist painting by Berthe Morisot that depicts a quiet, intimate moment of a woman absorbed in a book.
  • D. Read
    Read is a surname shared by various notable individuals across fields such as politics, arts, and academia.
  • E. Read
    Read is a village in Lancashire, England, situated near the River Calder and known for its residential community and local amenities.
  • 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_69d7bdec9f9c8190b4bac675b7588211 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9610fab488190ac6e6d5cf056ae37 completed April 10, 2026, 8:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6719886708190823f6f7e94e4d199 completed May 2, 2026, 9:50 p.m.
NEDg Description generation batch_69f6740129688190b286ce7acb4848c7 completed May 2, 2026, 10 p.m.
NED2 Entity disambiguation (via description) batch_69f675249d248190933421df49d3a2ab completed May 2, 2026, 10:05 p.m.
Created at: April 9, 2026, 5:15 p.m.