Triple

T10036862
Position Surface form Disambiguated ID Type / Status
Subject Anne Wiazemsky E205191 entity
Predicate notableWork P4 FINISHED
Object Marimé
Marimé is a novel by French writer and actress Anne Wiazemsky.
 E838021 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: Marimé | Statement: [Anne Wiazemsky, notableWork, Marimé]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Marimé
Context triple: [Anne Wiazemsky, notableWork, Marimé]
  • A. N’Guigmi
    N’Guigmi is a town and commune in southeastern Niger, located near Lake Chad and serving as an important local center for trade and transport.
  • B. Buema
    Buema is a locality situated within the Kufra region of southeastern Libya, an area known for its desert landscapes and oasis settlements.
  • C. Amandina
    Amandina is a feminine given name that functions as a variant form of Amanda.
  • D. Mouraria
    Mouraria is a historic Lisbon neighborhood known for its multicultural character, narrow medieval streets, and deep ties to traditional fado music.
  • E. Yassa
    Yassa was the codified legal and administrative code traditionally attributed to Genghis Khan that governed the Mongol Empire and its successor states.
  • 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: Marimé
Triple: [Anne Wiazemsky, notableWork, Marimé]
Generated description
Marimé is a novel by French writer and actress Anne Wiazemsky.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Marimé
Target entity description: Marimé is a novel by French writer and actress Anne Wiazemsky.
  • A. N’Guigmi
    N’Guigmi is a town and commune in southeastern Niger, located near Lake Chad and serving as an important local center for trade and transport.
  • B. Buema
    Buema is a locality situated within the Kufra region of southeastern Libya, an area known for its desert landscapes and oasis settlements.
  • C. Amandina
    Amandina is a feminine given name that functions as a variant form of Amanda.
  • D. Mouraria
    Mouraria is a historic Lisbon neighborhood known for its multicultural character, narrow medieval streets, and deep ties to traditional fado music.
  • E. Yassa
    Yassa was the codified legal and administrative code traditionally attributed to Genghis Khan that governed the Mongol Empire and its successor states.
  • 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_69ca834f70e88190b2d74828b7767ec1 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdcede428c8190ae115dc3425f9b0e completed April 2, 2026, 2:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69d28258ab088190a31ad5854d91193b completed April 5, 2026, 3:40 p.m.
NEDg Description generation batch_69d2867128ec8190a91cfc9def68c2be completed April 5, 2026, 3:57 p.m.
NED2 Entity disambiguation (via description) batch_69d286fdd2c88190b0ce5070c7875dcc completed April 5, 2026, 3:59 p.m.
Created at: March 30, 2026, 8:55 p.m.