Triple

T14887707
Position Surface form Disambiguated ID Type / Status
Subject Villingen-Schwenningen E359670 entity
Predicate twinTown P1072 FINISHED
Object Tula
Tula is a historic Russian city known for its metalworking, samovar production, and association with the writer Leo Tolstoy.
 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: [Villingen-Schwenningen, twinTown, Tula]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tula
Context triple: [Villingen-Schwenningen, twinTown, 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: [Villingen-Schwenningen, twinTown, Tula]
Generated description
Tula is a historic Russian city known for its metalworking, samovar production, and association with the writer Leo Tolstoy.
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, samovar production, and association with the writer Leo Tolstoy.
  • 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_69d827980cbc8190a0c569ae3940a1d9 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69ded5f5b1c88190815f3585770cb135 completed April 15, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe6b5f22c08190a9530cbd78cfc801 completed May 8, 2026, 11:01 p.m.
NEDg Description generation batch_69fe6f9b33748190aee0c27879866ca1 completed May 8, 2026, 11:19 p.m.
NED2 Entity disambiguation (via description) batch_69fe703e8c28819081b7bfe638a2202e completed May 8, 2026, 11:22 p.m.
Created at: April 10, 2026, 2:08 a.m.