Triple

T7699975
Position Surface form Disambiguated ID Type / Status
Subject Marie Pasteur E174465 entity
Predicate familyName P18 FINISHED
Object Laurent
Laurent is a French surname historically associated with various notable figures and families.
 E689388 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: Laurent | Statement: [Marie Pasteur, familyName, Laurent]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Laurent
Context triple: [Marie Pasteur, familyName, Laurent]
  • A. Laurent
    Laurent is a Belgian prince, the younger son of King Albert II and Queen Paola, known for his environmental interests and occasional public controversies.
  • B. Laurent
    Laurent is a central figure in Émile Zola’s novel "Thérèse Raquin," known as Thérèse’s lover and accomplice in a dark, psychologically driven crime.
  • C. Laurent
    Laurent is a nomadic vampire in the Twilight series who initially allies with James and Victoria before later attempting to betray the Cullens.
  • D. Benoît
    Benoît is the French form of the given name Benedict, commonly used in French-speaking countries.
  • E. Étienne
    Étienne is the given first name of the French Symbolist poet Stéphane Mallarmé.
  • 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: Laurent
Triple: [Marie Pasteur, familyName, Laurent]
Generated description
Laurent is a French surname historically associated with various notable figures and families.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Laurent
Target entity description: Laurent is a French surname historically associated with various notable figures and families.
  • A. Laurent
    Laurent is a Belgian prince, the younger son of King Albert II and Queen Paola, known for his environmental interests and occasional public controversies.
  • B. Laurent
    Laurent is a central figure in Émile Zola’s novel "Thérèse Raquin," known as Thérèse’s lover and accomplice in a dark, psychologically driven crime.
  • C. Laurent
    Laurent is a nomadic vampire in the Twilight series who initially allies with James and Victoria before later attempting to betray the Cullens.
  • D. Benoît
    Benoît is the French form of the given name Benedict, commonly used in French-speaking countries.
  • E. Étienne
    Étienne is the given first name of the French Symbolist poet Stéphane Mallarmé.
  • 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_69c6995a72cc8190998e56daa6f8e453 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7026ba7b48190a18f1c1cbbf1b944 completed March 27, 2026, 10:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8fa25e4a881909af09d8cbe6852dd completed March 29, 2026, 10:08 a.m.
NEDg Description generation batch_69c8fc426bf88190a97e55469daa56d6 completed March 29, 2026, 10:17 a.m.
NED2 Entity disambiguation (via description) batch_69c8fc5aca488190b52e8f0d336cda8e completed March 29, 2026, 10:18 a.m.
Created at: March 27, 2026, 4:03 p.m.