Triple

T1165945
Position Surface form Disambiguated ID Type / Status
Subject Lori Lightfoot E24799 entity
Predicate givenName P17 FINISHED
Object Lori
Lori is a feminine given name commonly used in English-speaking countries, often as a diminutive of Laura or Lorraine.
 E135112 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: Lori | Statement: [Lori Lightfoot, givenName, Lori]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lori
Context triple: [Lori Lightfoot, givenName, Lori]
  • A. Linda
    Linda is a feminine given name of Germanic origin that became widely used in English-speaking countries in the 20th century.
  • B. Lindsay
    Lindsay is the fugitive Australian protagonist of Gregory David Roberts' novel "Shantaram," who rebuilds his life in the underworld of Bombay.
  • C. Lindsey
    Lindsey is a given name commonly used in English-speaking countries for both females and males.
  • D. Lauren
    Lauren is a central female protagonist in the romantic comedy film "Think Like a Man," portrayed as a successful, relationship-seeking woman whose love life is influenced by Steve Harvey’s dating advice.
  • E. Kelly Grayson
    Kelly Grayson is a central character on the science fiction comedy series "The Orville," serving as the ship's first officer and the ex-wife of Captain Ed Mercer.
  • 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: Lori
Triple: [Lori Lightfoot, givenName, Lori]
Generated description
Lori is a feminine given name commonly used in English-speaking countries, often as a diminutive of Laura or Lorraine.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lori
Target entity description: Lori is a feminine given name commonly used in English-speaking countries, often as a diminutive of Laura or Lorraine.
  • A. Linda
    Linda is a feminine given name of Germanic origin that became widely used in English-speaking countries in the 20th century.
  • B. Lindsay
    Lindsay is the fugitive Australian protagonist of Gregory David Roberts' novel "Shantaram," who rebuilds his life in the underworld of Bombay.
  • C. Lindsey
    Lindsey is a given name commonly used in English-speaking countries for both females and males.
  • D. Lauren
    Lauren is a central female protagonist in the romantic comedy film "Think Like a Man," portrayed as a successful, relationship-seeking woman whose love life is influenced by Steve Harvey’s dating advice.
  • E. Kelly Grayson
    Kelly Grayson is a central character on the science fiction comedy series "The Orville," serving as the ship's first officer and the ex-wife of Captain Ed Mercer.
  • 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_69a494082a7c819095004f423f294a64 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bccc62a88190882d8801908015a4 completed March 1, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac6f17aa608190920b7df62b8dd903 completed March 7, 2026, 6:31 p.m.
NEDg Description generation batch_69ac6fc5442c8190a5d824881f05d468 completed March 7, 2026, 6:34 p.m.
NED2 Entity disambiguation (via description) batch_69ac7026dda48190a72f671dba9ac17b completed March 7, 2026, 6:36 p.m.
Created at: March 1, 2026, 7:45 p.m.