Triple

T9887534
Position Surface form Disambiguated ID Type / Status
Subject Lars Gyllensten E180972 entity
Predicate notableWork P4 FINISHED
Object Senilia
Senilia is a literary work by Swedish author and academic Lars Gyllensten, reflecting his characteristic blend of philosophical reflection and experimental prose.
 E827433 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: Senilia | Statement: [Lars Gyllensten, notableWork, Senilia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Senilia
Context triple: [Lars Gyllensten, notableWork, Senilia]
  • A. Sene
    Sene is the tenth month of the Ethiopian calendar, roughly corresponding to June in the Gregorian calendar.
  • B. Es Sénia
    Es Sénia is a commune and suburb of Oran in northwestern Algeria, known for hosting the region’s main international airport and various industrial and educational facilities.
  • C. Senesky
    Senesky is a surname most notably associated with George Senesky, an American professional basketball player and coach in the mid-20th century.
  • D. Gerenia
    Gerenia is an ancient town in Messenia, Greece, best known in Greek mythology as the homeland of the wise hero Nestor.
  • E. Elde
    The Elde is a river in northern Germany that flows through the state of Mecklenburg-Vorpommern and joins the Elbe, serving as an important regional waterway.
  • 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: Senilia
Triple: [Lars Gyllensten, notableWork, Senilia]
Generated description
Senilia is a literary work by Swedish author and academic Lars Gyllensten, reflecting his characteristic blend of philosophical reflection and experimental prose.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Senilia
Target entity description: Senilia is a literary work by Swedish author and academic Lars Gyllensten, reflecting his characteristic blend of philosophical reflection and experimental prose.
  • A. Sene
    Sene is the tenth month of the Ethiopian calendar, roughly corresponding to June in the Gregorian calendar.
  • B. Es Sénia
    Es Sénia is a commune and suburb of Oran in northwestern Algeria, known for hosting the region’s main international airport and various industrial and educational facilities.
  • C. Senesky
    Senesky is a surname most notably associated with George Senesky, an American professional basketball player and coach in the mid-20th century.
  • D. Gerenia
    Gerenia is an ancient town in Messenia, Greece, best known in Greek mythology as the homeland of the wise hero Nestor.
  • E. Elde
    The Elde is a river in northern Germany that flows through the state of Mecklenburg-Vorpommern and joins the Elbe, serving as an important regional waterway.
  • 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_69ca828082cc8190a40f8d299caa6545 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cdb457c8cc81909d211d5882228076 completed April 2, 2026, 12:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1eb0314108190b35906592a11727e completed April 5, 2026, 4:54 a.m.
NEDg Description generation batch_69d1ebec25508190ac4c0adb629f79b0 completed April 5, 2026, 4:58 a.m.
NED2 Entity disambiguation (via description) batch_69d1ec65d5e881909e4caa180b0f8867 completed April 5, 2026, 5 a.m.
Created at: March 30, 2026, 8:39 p.m.