Triple

T7175852
Position Surface form Disambiguated ID Type / Status
Subject Maçka campus E167316 entity
Predicate nearbyPlace P2064 FINISHED
Object Nişantaşı
Nişantaşı is an upscale neighborhood in Istanbul known for its luxury shopping streets, stylish cafes, and elegant residential buildings.
 E657402 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: Nişantaşı | Statement: [Maçka campus, nearbyPlace, Nişantaşı]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nişantaşı
Context triple: [Maçka campus, nearbyPlace, Nişantaşı]
  • A. Beştepe
    Beştepe is a neighborhood in Ankara, Turkey, best known as the site of the Turkish Presidential Complex.
  • B. Maltepe
    Maltepe is a residential and commercial district on Istanbul’s Asian side along the Sea of Marmara.
  • C. Eminönü
    Eminönü is a historic waterfront district in Istanbul known for its bustling ferry docks, spice and textile markets, and landmarks like the New Mosque and the Egyptian Bazaar.
  • D. Çankaya
    Çankaya is a central district of Ankara, Turkey, known for housing key government institutions, foreign embassies, and major national landmarks.
  • E. Brusa Bezistan
    Brusa Bezistan is a historic covered market building in Sarajevo’s old bazaar area, known for its Ottoman-era architecture and traditional trading stalls.
  • 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: Nişantaşı
Triple: [Maçka campus, nearbyPlace, Nişantaşı]
Generated description
Nişantaşı is an upscale neighborhood in Istanbul known for its luxury shopping streets, stylish cafes, and elegant residential buildings.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nişantaşı
Target entity description: Nişantaşı is an upscale neighborhood in Istanbul known for its luxury shopping streets, stylish cafes, and elegant residential buildings.
  • A. Beştepe
    Beştepe is a neighborhood in Ankara, Turkey, best known as the site of the Turkish Presidential Complex.
  • B. Maltepe
    Maltepe is a residential and commercial district on Istanbul’s Asian side along the Sea of Marmara.
  • C. Eminönü
    Eminönü is a historic waterfront district in Istanbul known for its bustling ferry docks, spice and textile markets, and landmarks like the New Mosque and the Egyptian Bazaar.
  • D. Çankaya
    Çankaya is a central district of Ankara, Turkey, known for housing key government institutions, foreign embassies, and major national landmarks.
  • E. Brusa Bezistan
    Brusa Bezistan is a historic covered market building in Sarajevo’s old bazaar area, known for its Ottoman-era architecture and traditional trading stalls.
  • 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_69c68889a2748190a316c5e65360361a completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e88ec6a8819083cbc3f4c39b8c79 completed March 27, 2026, 8:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7eec651a48190b52052bfef83ffcd completed March 28, 2026, 3:07 p.m.
NEDg Description generation batch_69c7f06173f481908faf95824827f1a9 completed March 28, 2026, 3:14 p.m.
NED2 Entity disambiguation (via description) batch_69c7f11f2b208190b235b9800a63faed completed March 28, 2026, 3:17 p.m.
Created at: March 27, 2026, 2:48 p.m.