Triple

T3917688
Position Surface form Disambiguated ID Type / Status
Subject Li Na E88883 entity
Predicate givenName P17 FINISHED
Object Na
Na is the given name of Chinese professional tennis player Li Na, a former world No. 2 and two-time Grand Slam singles champion.
 E400082 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: Na | Statement: [Li Na, givenName, Na]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Na
Context triple: [Li Na, givenName, Na]
  • A. Nu
    Nu is the given name of U Nu, the first Prime Minister of independent Burma (now Myanmar) and a prominent mid-20th-century political leader.
  • B. Ng
    Ng is a common Chinese surname found across various Chinese-speaking communities and the diaspora, often representing the Cantonese or Hokkien romanization of the character 吳 (Wu).
  • C. NA
    NA is the commonly used abbreviation for the National Assembly of Pakistan, the lower house of the country's bicameral parliament.
  • D. NH
    NH is the official two-letter United States Postal Service abbreviation for the state of New Hampshire.
  • E. NH
    NH is the two-letter IATA airline designator assigned to All Nippon Airways, Japan’s largest airline.
  • 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: Na
Triple: [Li Na, givenName, Na]
Generated description
Na is the given name of Chinese professional tennis player Li Na, a former world No. 2 and two-time Grand Slam singles champion.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Na
Target entity description: Na is the given name of Chinese professional tennis player Li Na, a former world No. 2 and two-time Grand Slam singles champion.
  • A. Nu
    Nu is the given name of U Nu, the first Prime Minister of independent Burma (now Myanmar) and a prominent mid-20th-century political leader.
  • B. Ng
    Ng is a common Chinese surname found across various Chinese-speaking communities and the diaspora, often representing the Cantonese or Hokkien romanization of the character 吳 (Wu).
  • C. NA
    NA is the commonly used abbreviation for the National Assembly of Pakistan, the lower house of the country's bicameral parliament.
  • D. NH
    NH is the official two-letter United States Postal Service abbreviation for the state of New Hampshire.
  • E. NH
    NH is the two-letter IATA airline designator assigned to All Nippon Airways, Japan’s largest airline.
  • 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_69aed955229881909e85e73ffab1d343 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeed5797508190adaddb84575d9bb3 completed March 9, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69b52864e0488190ab348a52cb9168b9 completed March 14, 2026, 9:20 a.m.
NEDg Description generation batch_69b52c3423988190aae6514041dc8ab3 completed March 14, 2026, 9:36 a.m.
NED2 Entity disambiguation (via description) batch_69b52ca9443481909e43a8bbe208c807 completed March 14, 2026, 9:38 a.m.
Created at: March 9, 2026, 3:22 p.m.