Triple

T19566858
Position Surface form Disambiguated ID Type / Status
Subject Mato Grosso E489604 entity
Predicate hasCity P316 FINISHED
Object Sinop
Sinop is a major agricultural and commercial city in the northern region of the Brazilian state of Mato Grosso.
E1383575 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: Sinop | Statement: [Mato Grosso, hasCity, Sinop]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sinop
Context triple: [Mato Grosso, hasCity, Sinop]
  • A. Sinop
    Sinop is a historic port city on Turkey’s Black Sea coast, long valued for its strategic harbor and role in regional trade and defense.
  • B. Sinop Province
    Sinop Province is a Black Sea coastal province in northern Turkey known for its historic port city of Sinop, natural landscapes, and maritime heritage.
  • C. Anamur
    Anamur is a coastal town and district in southern Turkey known for its banana production and historic Mamure Castle.
  • D. Sinope
    Sinope is an irregular, retrograde moon of Jupiter with a distant, eccentric orbit and a likely captured origin.
  • E. Dzhankoy
    Dzhankoy is a town in northern Crimea that serves as a key regional railway junction and transport hub.
  • 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: Sinop
Triple: [Mato Grosso, hasCity, Sinop]
Generated description
Sinop is a major agricultural and commercial city in the northern region of the Brazilian state of Mato Grosso.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sinop
Target entity description: Sinop is a major agricultural and commercial city in the northern region of the Brazilian state of Mato Grosso.
  • A. Sinop
    Sinop is a historic port city on Turkey’s Black Sea coast, long valued for its strategic harbor and role in regional trade and defense.
  • B. Sinop Province
    Sinop Province is a Black Sea coastal province in northern Turkey known for its historic port city of Sinop, natural landscapes, and maritime heritage.
  • C. Anamur
    Anamur is a coastal town and district in southern Turkey known for its banana production and historic Mamure Castle.
  • D. Sinope
    Sinope is an irregular, retrograde moon of Jupiter with a distant, eccentric orbit and a likely captured origin.
  • E. Dzhankoy
    Dzhankoy is a town in northern Crimea that serves as a key regional railway junction and transport hub.
  • 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e63f784ff88190a515c78429de3caf completed April 20, 2026, 3 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0757898214819090d82acf3fd830ff completed May 15, 2026, 5:27 p.m.
NEDg Description generation batch_6a075865eaac819085b35d165fda91d4 completed May 15, 2026, 5:31 p.m.
NED2 Entity disambiguation (via description) batch_6a07590b84488190a33889335ba95c95 completed May 15, 2026, 5:34 p.m.
Created at: April 10, 2026, 1:42 p.m.