Triple

T1525528
Position Surface form Disambiguated ID Type / Status
Subject Brida E32326 entity
Predicate character P662 FINISHED
Object Lorens
Lorens is a character from Paulo Coelho’s novel "Brida," serving as one of the key figures in the protagonist’s spiritual and personal journey.
 E174314 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: Lorens | Statement: [Brida, character, Lorens]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lorens
Context triple: [Brida, character, Lorens]
  • A. Larrelt
    Larrelt is a district of the German seaport city of Emden in Lower Saxony.
  • B. Lyness
    Lyness is a small coastal village and former naval base on the island of Hoy in Orkney, Scotland.
  • C. Loarki
    Loarki is a lesser-known dialect of the Rajasthani language spoken by specific communities in the northwestern Indian subcontinent.
  • D. Lorn
    Lorn is a residential suburb of Maitland in the Hunter Region of New South Wales, Australia, known for its historic homes and village-like atmosphere.
  • E. Loralai
    Loralai is a town and district in northern Balochistan, Pakistan, known historically as a regional administrative and trade center.
  • 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: Lorens
Triple: [Brida, character, Lorens]
Generated description
Lorens is a character from Paulo Coelho’s novel "Brida," serving as one of the key figures in the protagonist’s spiritual and personal journey.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lorens
Target entity description: Lorens is a character from Paulo Coelho’s novel "Brida," serving as one of the key figures in the protagonist’s spiritual and personal journey.
  • A. Larrelt
    Larrelt is a district of the German seaport city of Emden in Lower Saxony.
  • B. Lyness
    Lyness is a small coastal village and former naval base on the island of Hoy in Orkney, Scotland.
  • C. Loarki
    Loarki is a lesser-known dialect of the Rajasthani language spoken by specific communities in the northwestern Indian subcontinent.
  • D. Lorn
    Lorn is a residential suburb of Maitland in the Hunter Region of New South Wales, Australia, known for its historic homes and village-like atmosphere.
  • E. Loralai
    Loralai is a town and district in northern Balochistan, Pakistan, known historically as a regional administrative and trade center.
  • 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_69a885e9b0ac819093a9806ad0efc82c completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa61f7bb60819094774ecc632255de completed March 6, 2026, 5:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad2953c5308190984d20f62b7303fd completed March 8, 2026, 7:46 a.m.
NEDg Description generation batch_69ad2a1742d48190a82c1fc8c81d5c21 completed March 8, 2026, 7:49 a.m.
NED2 Entity disambiguation (via description) batch_69ad2aa092b08190930f1c39d963861b completed March 8, 2026, 7:52 a.m.
Created at: March 4, 2026, 7:26 p.m.