Triple

T9837345
Position Surface form Disambiguated ID Type / Status
Subject Caroline E239135 entity
Predicate hasDiminutive P456 FINISHED
Object Lina E757413 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: Lina | Statement: [Caroline, hasDiminutive, Lina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lina
Context triple: [Caroline, hasDiminutive, Lina]
  • A. Lina
    Lina is a Native American servant in Toni Morrison’s novel *A Mercy*, whose history of displacement and resilience reflects the novel’s themes of slavery, colonialism, and survival in 17th-century America.
  • B. Lina
    Lina Heydrich was the wife of high-ranking Nazi official Reinhard Heydrich and a committed supporter of National Socialism in Germany.
  • C. Lina
    Lina is a female lion character who serves as one of the official mascots for the Japanese professional baseball team Saitama Seibu Lions.
  • D. Lina chosen
    Lina is a feminine given name used in various cultures, often as a short form of names like Angelina, Karolina, or Alina.
  • E. Lucina
    Lucina is a woman known primarily as the mother of the Western Roman Emperor Anthemius.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69ca84e314108190978324a4bdb959f8 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb347ff4c81908c312548a25bae71 completed April 2, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1d5ccb28c8190a580767a57474557 completed April 5, 2026, 3:23 a.m.
Created at: March 30, 2026, 8:33 p.m.