Triple

T3276804
Position Surface form Disambiguated ID Type / Status
Subject Tatyana E68776 entity
Predicate hasDiminutiveForm P456 FINISHED
Object Tanya
Tanya is a common diminutive form of the female given name Tatyana, used in various Slavic and English-speaking contexts.
 E345341 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: Tanya | Statement: [Tatyana, hasDiminutiveForm, Tanya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tanya
Context triple: [Tatyana, hasDiminutiveForm, Tanya]
  • A. Tanya
    Tanya is the foundational Chabad-Lubavitch Hasidic work by Rabbi Shneur Zalman of Liadi, presenting a systematic approach to Jewish mysticism, psychology, and spiritual self-improvement.
  • B. Tessa
    Tessa is a feminine given name commonly used in English-speaking countries, often as a diminutive of Theresa or Therese.
  • C. Jenny
    "Jenny" is a narrative poem by Dante Gabriel Rossetti that explores themes of desire, morality, and Victorian attitudes toward prostitution through a reflective monologue addressed to a fallen woman.
  • D. Jenny
    Jenny is a caring and protective regal blue tang fish who is Dory’s mother in the animated film "Finding Dory."
  • E. Tamara
    Tamara is a feminine given name of Hebrew origin, commonly used in various cultures and languages.
  • 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: Tanya
Triple: [Tatyana, hasDiminutiveForm, Tanya]
Generated description
Tanya is a common diminutive form of the female given name Tatyana, used in various Slavic and English-speaking contexts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tanya
Target entity description: Tanya is a common diminutive form of the female given name Tatyana, used in various Slavic and English-speaking contexts.
  • A. Tanya
    Tanya is the foundational Chabad-Lubavitch Hasidic work by Rabbi Shneur Zalman of Liadi, presenting a systematic approach to Jewish mysticism, psychology, and spiritual self-improvement.
  • B. Tessa
    Tessa is a feminine given name commonly used in English-speaking countries, often as a diminutive of Theresa or Therese.
  • C. Jenny
    "Jenny" is a narrative poem by Dante Gabriel Rossetti that explores themes of desire, morality, and Victorian attitudes toward prostitution through a reflective monologue addressed to a fallen woman.
  • D. Jenny
    Jenny is a caring and protective regal blue tang fish who is Dory’s mother in the animated film "Finding Dory."
  • E. Tamara
    Tamara is a feminine given name of Hebrew origin, commonly used in various cultures and languages.
  • 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_69ad859b54f881909bf530d549caf2fd completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb0128f08819084644f3c8fda2596 completed March 8, 2026, 5:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2e84a3c2c8190908152fc042fcad1 completed March 12, 2026, 4:22 p.m.
NEDg Description generation batch_69b2e939460481909743b49e274b693e completed March 12, 2026, 4:26 p.m.
NED2 Entity disambiguation (via description) batch_69b2ecfd3c20819089bc0b2141aee8eb completed March 12, 2026, 4:42 p.m.
Created at: March 8, 2026, 3:10 p.m.