Triple

T735519
Position Surface form Disambiguated ID Type / Status
Subject Chan E14920 entity
Predicate hasVariantSpelling P457 FINISHED
Object Tan
Tan is a surname and given name commonly found in various East and Southeast Asian cultures, often representing a romanization of different Chinese family names.
 E87692 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: Tan | Statement: [Chan, hasVariantSpelling, Tan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tan
Context triple: [Chan, hasVariantSpelling, Tan]
  • A. Tur
    Tur is a foundational 14th-century Jewish legal code by Rabbi Jacob ben Asher that systematically organized halakhic rulings and served as a primary basis for later works like the Shulchan Aruch.
  • B. Tony
    The Tony is a prestigious American theater award presented annually to recognize excellence in Broadway productions.
  • C. Tyler
    Tyler is the officer in a Masonic lodge responsible for guarding the entrance and ensuring only qualified individuals are admitted to meetings.
  • D. Tipai
    Tipai is a Yuman language variety traditionally spoken by the Tipai people of northern Baja California and southern California, closely related to other Kumeyaay dialects.
  • E. Chan
    Chan is a common Chinese surname shared by many notable individuals across various fields worldwide.
  • 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: Tan
Triple: [Chan, hasVariantSpelling, Tan]
Generated description
Tan is a surname and given name commonly found in various East and Southeast Asian cultures, often representing a romanization of different Chinese family names.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tan
Target entity description: Tan is a surname and given name commonly found in various East and Southeast Asian cultures, often representing a romanization of different Chinese family names.
  • A. Tur
    Tur is a foundational 14th-century Jewish legal code by Rabbi Jacob ben Asher that systematically organized halakhic rulings and served as a primary basis for later works like the Shulchan Aruch.
  • B. Tony
    The Tony is a prestigious American theater award presented annually to recognize excellence in Broadway productions.
  • C. Tyler
    Tyler is the officer in a Masonic lodge responsible for guarding the entrance and ensuring only qualified individuals are admitted to meetings.
  • D. Tipai
    Tipai is a Yuman language variety traditionally spoken by the Tipai people of northern Baja California and southern California, closely related to other Kumeyaay dialects.
  • E. Chan
    Chan is a common Chinese surname shared by many notable individuals across various fields worldwide.
  • 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_69a4934d9930819099eed80096b0597d completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a5da30b88190afbd12ae6109cc1b completed March 1, 2026, 8:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69a64a5f0de4819083457c86e5e93ba0 completed March 3, 2026, 2:41 a.m.
NEDg Description generation batch_69a64b03246081908c20445a7a401008 completed March 3, 2026, 2:44 a.m.
NED2 Entity disambiguation (via description) batch_69a64b4e9cec8190a3dcc378f853be0d completed March 3, 2026, 2:45 a.m.
Created at: March 1, 2026, 7:37 p.m.