Triple

T12128791
Position Surface form Disambiguated ID Type / Status
Subject Mersin Province E288878 entity
Predicate hasDistrict P459 FINISHED
Object Toroslar
Toroslar is a district and municipality in southern Turkey known for its mountainous terrain and proximity to the city of Mersin.
E967917 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: Toroslar | Statement: [Mersin Province, hasDistrict, Toroslar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toroslar
Context triple: [Mersin Province, hasDistrict, Toroslar]
  • A. Toros
    Toros is the nickname of Major League Soccer club FC Dallas, reflecting the team's bull-themed identity.
  • B. Toros
    The Toros are the athletic teams representing California State University, Dominguez Hills in intercollegiate sports.
  • C. Toros
    Toros is the abbreviated name of the Austin Toros, a professional basketball team that competed in the NBA Development League.
  • D. Toros
    Toros is the short name of the Toronto Toros, a former World Hockey Association team based in Toronto, Canada.
  • E. Bull
    Bull was the notorious nickname of Eugene "Bull" Connor, the Birmingham, Alabama public safety commissioner whose brutal enforcement of racial segregation during the Civil Rights Movement made him a national symbol of racist oppression.
  • 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: Toroslar
Triple: [Mersin Province, hasDistrict, Toroslar]
Generated description
Toroslar is a district and municipality in southern Turkey known for its mountainous terrain and proximity to the city of Mersin.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Toroslar
Target entity description: Toroslar is a district and municipality in southern Turkey known for its mountainous terrain and proximity to the city of Mersin.
  • A. Toros
    Toros is the nickname of Major League Soccer club FC Dallas, reflecting the team's bull-themed identity.
  • B. Toros
    The Toros are the athletic teams representing California State University, Dominguez Hills in intercollegiate sports.
  • C. Toros
    Toros is the abbreviated name of the Austin Toros, a professional basketball team that competed in the NBA Development League.
  • D. Toros
    Toros is the short name of the Toronto Toros, a former World Hockey Association team based in Toronto, Canada.
  • E. Bull
    Bull was the notorious nickname of Eugene "Bull" Connor, the Birmingham, Alabama public safety commissioner whose brutal enforcement of racial segregation during the Civil Rights Movement made him a national symbol of racist oppression.
  • 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_69d6ab4b5e4c81909950b17151eb0951 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9158a2c2c8190aaff9d0cce177565 completed April 10, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f68ac15c81908388dd3194e9dfc4 completed May 2, 2026, 1:05 p.m.
NEDg Description generation batch_69f6048d6f24819093862fb46f9938f1 completed May 2, 2026, 2:05 p.m.
NED2 Entity disambiguation (via description) batch_69f6056e3fdc81908e6e97c4c37a18bb completed May 2, 2026, 2:08 p.m.
Created at: April 8, 2026, 9:49 p.m.