Triple

T11601562
Position Surface form Disambiguated ID Type / Status
Subject Lorenz E275141 entity
Predicate relatedName P3889 FINISHED
Object Laurent unclear NED1 NE FINISHED

How this triple was built (2 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: [Lorenz, relatedName, Laurent]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laurent
Context triple: [Lorenz, relatedName, 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. Laurent
    Laurent is a French surname historically associated with various notable figures and families.
  • E. Laurent
    Laurent is a French given name, commonly used as the French form of Lawrence.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

Provenance (3 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_69d6aae6b14c81908dc5a74bad7591f9 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8954daa908190a8d532e43aa4a881 completed April 10, 2026, 6:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69ee87077d008190874a8339b64dd5ec completed April 26, 2026, 9:43 p.m.
Created at: April 8, 2026, 9:38 p.m.