Triple

T7175785
Position Surface form Disambiguated ID Type / Status
Subject Maslak campus E167314 entity
Predicate district P2709 FINISHED
Object Maslak
Maslak is a major business and financial district in Istanbul, Turkey, known for its skyscrapers, corporate offices, and modern commercial complexes.
 E646551 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: Maslak | Statement: [Maslak campus, district, Maslak]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Maslak
Context triple: [Maslak campus, district, Maslak]
  • A. Yenimahalle
    Yenimahalle is a major district of Ankara, Turkey, known for hosting key government institutions and residential areas within the capital.
  • B. Bakırköy
    Bakırköy is a coastal district on the European side of Istanbul, Turkey, known for its residential neighborhoods, shopping centers, and seaside recreation areas.
  • C. Ortaköy
    Ortaköy is a lively Bosphorus-side neighborhood in Istanbul known for its waterfront mosque, cafes, and views of the Bosporus Bridge.
  • D. Sincan
    Sincan is a district and rapidly growing suburban area of Turkey’s capital region, located to the west of central Ankara.
  • E. Etimesgut
    Etimesgut is a rapidly growing suburban district and municipality on the western side of Ankara, Turkey’s capital city.
  • 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: Maslak
Triple: [Maslak campus, district, Maslak]
Generated description
Maslak is a major business and financial district in Istanbul, Turkey, known for its skyscrapers, corporate offices, and modern commercial complexes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Maslak
Target entity description: Maslak is a major business and financial district in Istanbul, Turkey, known for its skyscrapers, corporate offices, and modern commercial complexes.
  • A. Yenimahalle
    Yenimahalle is a major district of Ankara, Turkey, known for hosting key government institutions and residential areas within the capital.
  • B. Bakırköy
    Bakırköy is a coastal district on the European side of Istanbul, Turkey, known for its residential neighborhoods, shopping centers, and seaside recreation areas.
  • C. Ortaköy
    Ortaköy is a lively Bosphorus-side neighborhood in Istanbul known for its waterfront mosque, cafes, and views of the Bosporus Bridge.
  • D. Sincan
    Sincan is a district and rapidly growing suburban area of Turkey’s capital region, located to the west of central Ankara.
  • E. Etimesgut
    Etimesgut is a rapidly growing suburban district and municipality on the western side of Ankara, Turkey’s capital city.
  • 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_69c7b9281e808190ac2a8ad585a70ea0 completed March 28, 2026, 11:19 a.m.
NEDg Description generation batch_69c7b9993f40819098c59865a3e64532 completed March 28, 2026, 11:20 a.m.
NED2 Entity disambiguation (via description) batch_69c7ba4f196c8190b29e6ddc091f11a6 completed March 28, 2026, 11:23 a.m.
Created at: March 27, 2026, 2:48 p.m.