Triple

T13251230
Position Surface form Disambiguated ID Type / Status
Subject Kızılay E315533 entity
Predicate locatedNear P294 FINISHED
Object Sıhhiye
Sıhhiye is a central district and major transportation hub in Ankara, Turkey, known for its government buildings, hospitals, and busy urban thoroughfares.
E1085317 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: Sıhhiye | Statement: [Kızılay, locatedNear, Sıhhiye]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sıhhiye
Context triple: [Kızılay, locatedNear, Sıhhiye]
  • A. Güzelyurt
    Güzelyurt is a town in the northwestern part of Cyprus, known for its citrus orchards and archaeological sites.
  • B. Güzelyurt
    Güzelyurt is a historic town in Turkey’s Cappadocia region, known for its rock-cut churches, underground cities, and scenic valleys.
  • C. Sivrice
    Sivrice is a small town and district in eastern Turkey known for its location on the shores of Lake Hazar in Elazığ Province.
  • D. Orhangazi
    Orhangazi is a town and district in northwestern Turkey known for its olive cultivation and location near Lake İznik in Bursa Province.
  • E. İnhisar
    İnhisar is a small town and district located in Turkey's Bilecik Province in the Marmara region.
  • 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: Sıhhiye
Triple: [Kızılay, locatedNear, Sıhhiye]
Generated description
Sıhhiye is a central district and major transportation hub in Ankara, Turkey, known for its government buildings, hospitals, and busy urban thoroughfares.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sıhhiye
Target entity description: Sıhhiye is a central district and major transportation hub in Ankara, Turkey, known for its government buildings, hospitals, and busy urban thoroughfares.
  • A. Güzelyurt
    Güzelyurt is a town in the northwestern part of Cyprus, known for its citrus orchards and archaeological sites.
  • B. Güzelyurt
    Güzelyurt is a historic town in Turkey’s Cappadocia region, known for its rock-cut churches, underground cities, and scenic valleys.
  • C. Sivrice
    Sivrice is a small town and district in eastern Turkey known for its location on the shores of Lake Hazar in Elazığ Province.
  • D. Orhangazi
    Orhangazi is a town and district in northwestern Turkey known for its olive cultivation and location near Lake İznik in Bursa Province.
  • E. İnhisar
    İnhisar is a small town and district located in Turkey's Bilecik Province in the Marmara region.
  • 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_69d806b1072881909e46bd212259c5f0 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98f73423c8190932a9edac56df383 completed April 11, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd19226eb881908f76134a04e72548 completed May 7, 2026, 10:58 p.m.
NEDg Description generation batch_69fd1bdca600819081ee087a071f7684 completed May 7, 2026, 11:10 p.m.
NED2 Entity disambiguation (via description) batch_69fd1cb6d2b88190a5976197144277f6 completed May 7, 2026, 11:13 p.m.
Created at: April 9, 2026, 9:24 p.m.