Triple

T13880910
Position Surface form Disambiguated ID Type / Status
Subject Maria Ouspenskaya E333711 entity
Predicate placeOfBirth P1 FINISHED
Object Tula
Tula is a historic Russian city known for its metalworking, armaments industry, and association with writer Leo Tolstoy’s nearby estate, Yasnaya Polyana.
 E111344 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: Tula | Statement: [Maria Ouspenskaya, placeOfBirth, Tula]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tula
Context triple: [Maria Ouspenskaya, placeOfBirth, Tula]
  • A. Tula
    Tula is the birth name of American actress and dancer Cyd Charisse, famed for her roles in classic Hollywood musicals.
  • B. Tula
    Tula is a small coastal village in the Eastern District of American Samoa known for its traditional Samoan culture and scenic Pacific island setting.
  • C. Tula
    Tula is a town in the Logudoro region of northern Sardinia, Italy, known for its rural landscape and traditional Sardinian culture.
  • D. Tula
    Tula is the given name of British singer, songwriter, and television personality Tulisa Contostavlos, known for her work with N-Dubz and as a judge on The X Factor UK.
  • E. Tula
    Tula is an important ancient Mesoamerican city, once a major Toltec capital known for its monumental architecture and iconic stone warrior statues.
  • 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: Tula
Triple: [Maria Ouspenskaya, placeOfBirth, Tula]
Generated description
Tula is a historic Russian city known for its metalworking, armaments industry, and association with writer Leo Tolstoy’s nearby estate, Yasnaya Polyana.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tula
Target entity description: Tula is a historic Russian city known for its metalworking, armaments industry, and association with writer Leo Tolstoy’s nearby estate, Yasnaya Polyana.
  • A. Tula chosen
    Tula is a historic Russian city south of Moscow, known for its metalworking, samovar production, and as a cultural center near Leo Tolstoy’s estate at Yasnaya Polyana.
  • B. Tula
    Tula is an important ancient Mesoamerican city, once a major Toltec capital known for its monumental architecture and iconic stone warrior statues.
  • C. Tula
    Tula is a town in the Logudoro region of northern Sardinia, Italy, known for its rural landscape and traditional Sardinian culture.
  • D. Tula
    Tula is a small coastal village in the Eastern District of American Samoa known for its traditional Samoan culture and scenic Pacific island setting.
  • E. Tula
    Tula is the given name of British singer, songwriter, and television personality Tulisa Contostavlos, known for her work with N-Dubz and as a judge on The X Factor UK.
  • F. None of above.

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_69d81c5dd2d48190b7a5fc1e009de936 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0be8566881908b8902e3cd567669 completed April 14, 2026, 9:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c711f9b08190aa5981320597e83b completed May 3, 2026, 10:07 p.m.
NEDg Description generation batch_69f7c7e1247481908073c1e282c3619f completed May 3, 2026, 10:10 p.m.
NED2 Entity disambiguation (via description) batch_69f7c8f5675c8190906f37cee6d8c493 completed May 3, 2026, 10:15 p.m.
Created at: April 9, 2026, 10:15 p.m.