Triple

T14672053
Position Surface form Disambiguated ID Type / Status
Subject Ilse E344536 entity
Predicate hasRelatedName P3889 FINISHED
Object Lisa
Lisa is a common given name used in many cultures, often as a short form of Elisabeth.
 E300630 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: Lisa | Statement: [Ilse, hasRelatedName, Lisa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lisa
Context triple: [Ilse, hasRelatedName, Lisa]
  • A. Lisa
    Lisa is the central protagonist of the film "Wicker Park," around whom the story’s romantic mystery and emotional tension revolve.
  • B. Lisa
    Lisa is a central character in the science fiction adventure film "Zathura: A Space Adventure," where she becomes unwittingly involved in her younger brothers' perilous journey through outer space.
  • C. Lisa
    Lisa is a custom-designed integrated circuit that served as a key support chipset component in early Apple Macintosh computers, handling functions such as memory and system control.
  • D. Lisa
    Lisa is a person known primarily for holding a position or role that was later taken over by Denise.
  • E. Lisa
    "Lisa" is a notable work by control theorist and Stanford professor Stephen Boyd, likely associated with his research in optimization and control systems.
  • 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: Lisa
Triple: [Ilse, hasRelatedName, Lisa]
Generated description
Lisa is a common given name used in many cultures, often as a short form of Elisabeth.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lisa
Target entity description: Lisa is a common given name used in many cultures, often as a short form of Elisabeth.
  • A. Lisa chosen
    Lisa is a feminine given name commonly used in English-speaking countries, often as a shortened form of Elizabeth or Melissa.
  • B. Lisa
    Lisa is a person known primarily for holding a position or role that was later taken over by Denise.
  • C. Lisa
    Lisa is a fictional character known primarily as the romantic interest of Luke.
  • D. Lisa
    Lisa is the given name of Australian musician and composer Lisa Gerrard, renowned for her work as part of Dead Can Dance and for her film scores.
  • E. Lisa
    Lisa is a close friend and confidante of Sophie Sheridan in the Mamma Mia! universe.
  • 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_69d822e283fc8190a0e4c235cf880052 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb55064cc8190b9669d0b2da61825 completed April 14, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69fde17a39b88190b144b6cfcc61a4b8 completed May 8, 2026, 1:13 p.m.
NEDg Description generation batch_69fde447189881909b4b0dc654a05e0d completed May 8, 2026, 1:25 p.m.
NED2 Entity disambiguation (via description) batch_69fde53290a48190b3701472bb4e3d63 completed May 8, 2026, 1:29 p.m.
Created at: April 10, 2026, 1:27 a.m.