Triple

T22210766
Position Surface form Disambiguated ID Type / Status
Subject Lena Olin E548937 entity
Predicate givenName P17 FINISHED
Object Lena
Lena is a feminine given name used in various cultures, often as a shortened form of names like Helena or Magdalena.
E200105 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: Lena | Statement: [Lena Olin, givenName, Lena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lena
Context triple: [Lena Olin, givenName, Lena]
  • A. Lena
    Lena is an alternate given name of Lee Krasner, the influential American abstract expressionist painter and wife of Jackson Pollock.
  • B. Lena
    Lena is the central female protagonist in Pedro Almodóvar’s 2009 Spanish drama film "Broken Embraces," portrayed by Penélope Cruz.
  • C. Lena
    Lena is a central character in the work "Entre Nous," around whom much of the story’s emotional and narrative focus revolves.
  • D. Lena
    Lena is a central female character in François Truffaut’s film "Shoot the Piano Player," serving as a key romantic interest and catalyst in the story’s blend of crime, drama, and melancholy.
  • E. Lena
    Lena is a settlement in the municipality of Toten in Innlandet county, Norway.
  • 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: Lena
Triple: [Lena Olin, givenName, Lena]
Generated description
Lena is a feminine given name used in various cultures, often as a shortened form of names like Helena or Magdalena.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lena
Target entity description: Lena is a feminine given name used in various cultures, often as a shortened form of names like Helena or Magdalena.
  • A. Lena chosen
    Lena is a common feminine given name used in many languages, often derived from longer names such as Magdalena or Helena.
  • B. Lena
    Lena is an alternate given name of Lee Krasner, the influential American abstract expressionist painter and wife of Jackson Pollock.
  • C. Lena
    Lena is a central character in the work "Entre Nous," around whom much of the story’s emotional and narrative focus revolves.
  • D. Lena
    Lena is a municipality and town located in the Asturian mining region of northern Spain, known for its mountainous landscape and industrial heritage.
  • E. Lena
    Lena is a central female character in François Truffaut’s film "Shoot the Piano Player," serving as a key romantic interest and catalyst in the story’s blend of crime, drama, and melancholy.
  • F. None of above.

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_69e11e3f7e04819089806d81d5ac431e completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f12b2bcf748190a9721f0c9ae17e70 completed April 28, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0aa61cc9e48190ba5f6eb2a7cf3c9b completed May 18, 2026, 5:39 a.m.
NEDg Description generation batch_6a0aa6c001d48190b49866f02514aa28 completed May 18, 2026, 5:42 a.m.
NED2 Entity disambiguation (via description) batch_6a0aa74204a081909fa0d80858bfa6bb completed May 18, 2026, 5:44 a.m.
Created at: April 16, 2026, 8:36 p.m.