Triple

T234644
Position Surface form Disambiguated ID Type / Status
Subject The New York Times E4481 entity
Predicate nickname P55 FINISHED
Object The Gray Lady
The Gray Lady is a longstanding nickname for The New York Times, reflecting its reputation as a serious, authoritative, and traditional American newspaper.
 E30079 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: The Gray Lady | Statement: [The New York Times, nickname, The Gray Lady]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: The Gray Lady
Context triple: [The New York Times, nickname, The Gray Lady]
  • A. The Browning Version
    The Browning Version is a 1948 stage play by British dramatist Terence Rattigan that portrays the emotional and professional decline of a repressed, aging schoolmaster at an English public school.
  • B. Shirley
    Shirley is a small town in north-central Massachusetts served by commuter rail on the MBTA Fitchburg Line.
  • C. Shirley
    Shirley is an English surname of Old English origin that has also become a common given name.
  • D. Shirley
    Shirley is the given name of Shirley Ann Jackson, a prominent American physicist and trailblazing academic leader.
  • E. Madam
    "Madam" is a formal term of address for a woman, often used to show respect or politeness in social, professional, or official contexts.
  • 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: The Gray Lady
Triple: [The New York Times, nickname, The Gray Lady]
Generated description
The Gray Lady is a longstanding nickname for The New York Times, reflecting its reputation as a serious, authoritative, and traditional American newspaper.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: The Gray Lady
Target entity description: The Gray Lady is a longstanding nickname for The New York Times, reflecting its reputation as a serious, authoritative, and traditional American newspaper.
  • A. The Browning Version
    The Browning Version is a 1948 stage play by British dramatist Terence Rattigan that portrays the emotional and professional decline of a repressed, aging schoolmaster at an English public school.
  • B. Shirley
    Shirley is a small town in north-central Massachusetts served by commuter rail on the MBTA Fitchburg Line.
  • C. Shirley
    Shirley is an English surname of Old English origin that has also become a common given name.
  • D. Shirley
    Shirley is the given name of Shirley Ann Jackson, a prominent American physicist and trailblazing academic leader.
  • E. Madam
    "Madam" is a formal term of address for a woman, often used to show respect or politeness in social, professional, or official contexts.
  • 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_69a257363ffc81909757bde7ab3404da completed Feb. 28, 2026, 2:47 a.m.
NER Named-entity recognition batch_69a25cc9ab2c81909af278a07f86aa1e completed Feb. 28, 2026, 3:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69a36478ebcc8190b95419be9bc6bba3 completed Feb. 28, 2026, 9:56 p.m.
NEDg Description generation batch_69a3651d2b108190a81d8c3076f6e617 completed Feb. 28, 2026, 9:58 p.m.
NED2 Entity disambiguation (via description) batch_69a3657903608190988a4c933bbc262c completed Feb. 28, 2026, 10 p.m.
Created at: Feb. 28, 2026, 2:53 a.m.