Triple

T1435470
Position Surface form Disambiguated ID Type / Status
Subject Boğaziçi University E30550 entity
Predicate locatedIn P40 FINISHED
Object Bebek
Bebek is an upscale seaside neighborhood on Istanbul’s Bosphorus shore, known for its scenic views, cafes, and vibrant social life.
 E163551 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: Bebek | Statement: [Boğaziçi University, locatedIn, Bebek]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bebek
Context triple: [Boğaziçi University, locatedIn, Bebek]
  • A. Beba
    Beba is a city in Egypt’s Beni Suef Governorate, known as a local administrative and commercial center in the region.
  • B. Bubi
    Bubi is the nickname of Erich Hartmann, the German World War II fighter pilot who became history’s highest-scoring flying ace.
  • C. Beibei
    Beibei is one of the five Fuwa mascots of the 2008 Beijing Summer Olympics, symbolizing prosperity and representing the element of water.
  • D. Poike
    Poike is one of the three main extinct volcanic cones that form the triangular shape of Easter Island in the southeastern Pacific Ocean.
  • E. Bube
    Bube is a Bantu language spoken primarily by the Bubi people on Bioko Island in Equatorial Guinea.
  • 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: Bebek
Triple: [Boğaziçi University, locatedIn, Bebek]
Generated description
Bebek is an upscale seaside neighborhood on Istanbul’s Bosphorus shore, known for its scenic views, cafes, and vibrant social life.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bebek
Target entity description: Bebek is an upscale seaside neighborhood on Istanbul’s Bosphorus shore, known for its scenic views, cafes, and vibrant social life.
  • A. Beba
    Beba is a city in Egypt’s Beni Suef Governorate, known as a local administrative and commercial center in the region.
  • B. Bubi
    Bubi is the nickname of Erich Hartmann, the German World War II fighter pilot who became history’s highest-scoring flying ace.
  • C. Beibei
    Beibei is one of the five Fuwa mascots of the 2008 Beijing Summer Olympics, symbolizing prosperity and representing the element of water.
  • D. Poike
    Poike is one of the three main extinct volcanic cones that form the triangular shape of Easter Island in the southeastern Pacific Ocean.
  • E. Bube
    Bube is a Bantu language spoken primarily by the Bubi people on Bioko Island in Equatorial Guinea.
  • 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_69a498fc69ec8190b61722bd4b67c4d2 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c50250b88190a0fcf3e0cbba0b1a completed March 1, 2026, 11 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad017084908190a81a784ae4a53c21 completed March 8, 2026, 4:56 a.m.
NEDg Description generation batch_69ad0259651c8190890e45c1786a9a50 completed March 8, 2026, 5 a.m.
NED2 Entity disambiguation (via description) batch_69ad03018aa4819090020ba89a11d0cd completed March 8, 2026, 5:02 a.m.
Created at: March 1, 2026, 8 p.m.