Triple

T20029014
Position Surface form Disambiguated ID Type / Status
Subject Podolsk railway station E495069 entity
Predicate connectsTo P845 FINISHED
Object Tula
Tula is a historic industrial city in western Russia, renowned for its weapons manufacturing, samovars, and gingerbread.
 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: [Podolsk railway station, connectsTo, Tula]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tula
Context triple: [Podolsk railway station, connectsTo, 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: [Podolsk railway station, connectsTo, Tula]
Generated description
Tula is a historic industrial city in western Russia, renowned for its weapons manufacturing, samovars, and gingerbread.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tula
Target entity description: Tula is a historic industrial city in western Russia, renowned for its weapons manufacturing, samovars, and gingerbread.
  • 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_69da626bfd288190aa5d65098b6433ae completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e662908df081909a6c8ccf0dd90fff completed April 20, 2026, 5:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0815faba4c81908e8f3f97ef72dea2 completed May 16, 2026, 7 a.m.
NEDg Description generation batch_6a08174e741081908917c18b62547842 completed May 16, 2026, 7:05 a.m.
NED2 Entity disambiguation (via description) batch_6a0817ada884819087624c3788d0c6e0 completed May 16, 2026, 7:07 a.m.
Created at: April 11, 2026, 3:36 p.m.