Triple

T9131611
Position Surface form Disambiguated ID Type / Status
Subject Norm Lewis E219099 entity
Predicate givenName P17 FINISHED
Object Norm
Norm is a masculine given name, often a shortened form of Norman, commonly used in English-speaking countries.
 E780216 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: Norm | Statement: [Norm Lewis, givenName, Norm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Norm
Context triple: [Norm Lewis, givenName, Norm]
  • A. Normal
    Normal is a Mexico City Metro station on Line 2 that serves the San Rafael neighborhood near several educational institutions.
  • B. Normal
    Normal is a central Illinois town best known as the home of Illinois State University and part of the twin-city community with Bloomington.
  • C. Nut
    Nut is the ancient Egyptian sky goddess, often depicted arching over the earth and associated with the heavens, stars, and the cyclical rebirth of the sun.
  • D. NER
    NER is the three-letter ISO 3166-1 alpha-3 country code assigned to the Republic of Niger.
  • E. NER
    NER is a commonly used abbreviation for Northeast India, a culturally diverse and geographically distinct region of the country comprising its easternmost states.
  • 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: Norm
Triple: [Norm Lewis, givenName, Norm]
Generated description
Norm is a masculine given name, often a shortened form of Norman, commonly used in English-speaking countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Norm
Target entity description: Norm is a masculine given name, often a shortened form of Norman, commonly used in English-speaking countries.
  • A. Normal
    Normal is a central Illinois town best known as the home of Illinois State University and part of the twin-city community with Bloomington.
  • B. Normal
    Normal is a Mexico City Metro station on Line 2 that serves the San Rafael neighborhood near several educational institutions.
  • C. Nut
    Nut is the ancient Egyptian sky goddess, often depicted arching over the earth and associated with the heavens, stars, and the cyclical rebirth of the sun.
  • D. NER
    NER is the three-letter ISO 3166-1 alpha-3 country code assigned to the Republic of Niger.
  • E. NER
    NER is a commonly used abbreviation for Northeast India, a culturally diverse and geographically distinct region of the country comprising its easternmost states.
  • 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_69ca83debfc0819095800583e97ab10f completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca8ceea6c81909f368f12dac1649c completed April 1, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d047dc25208190a720910e6d43199b completed April 3, 2026, 11:06 p.m.
NEDg Description generation batch_69d049058dec81909854965276252808 completed April 3, 2026, 11:11 p.m.
NED2 Entity disambiguation (via description) batch_69d049913b7481909ccbaf4999e37c06 completed April 3, 2026, 11:13 p.m.
Created at: March 30, 2026, 7:18 p.m.