Triple

T11978367
Position Surface form Disambiguated ID Type / Status
Subject Menderes E285092 entity
Predicate contains P35 FINISHED
Object Ahmetbeyli
Ahmetbeyli is a coastal neighborhood and historical area in western Turkey known for its beaches and proximity to ancient ruins.
 E958007 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: Ahmetbeyli | Statement: [Menderes, contains, Ahmetbeyli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ahmetbeyli
Context triple: [Menderes, contains, Ahmetbeyli]
  • A. Bekir
    Bekir is a common Turkish male given name of Arabic origin, often associated with early Islamic history and frequently borne by notable figures in Turkey.
  • B. Ahmet
    Ahmet is a common male given name of Arabic origin, widely used in Turkey and other Muslim-majority countries as a variant of Ahmed.
  • C. Zübeyir
    Zübeyir is a Turkish masculine given name, notably borne by the archaeologist and ethnographer Hamit Zübeyir Koşay.
  • D. Kerim Bey
    Kerim Bey is a charismatic and resourceful MI6 ally in the James Bond series, best known for assisting Bond in Istanbul in the film and novel "From Russia, with Love."
  • E. Melikgazi
    Melikgazi is a central district and municipality of the city of Kayseri in central Turkey, known as one of the province’s main urban and administrative hubs.
  • 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: Ahmetbeyli
Triple: [Menderes, contains, Ahmetbeyli]
Generated description
Ahmetbeyli is a coastal neighborhood and historical area in western Turkey known for its beaches and proximity to ancient ruins.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ahmetbeyli
Target entity description: Ahmetbeyli is a coastal neighborhood and historical area in western Turkey known for its beaches and proximity to ancient ruins.
  • A. Bekir
    Bekir is a common Turkish male given name of Arabic origin, often associated with early Islamic history and frequently borne by notable figures in Turkey.
  • B. Ahmet
    Ahmet is a common male given name of Arabic origin, widely used in Turkey and other Muslim-majority countries as a variant of Ahmed.
  • C. Zübeyir
    Zübeyir is a Turkish masculine given name, notably borne by the archaeologist and ethnographer Hamit Zübeyir Koşay.
  • D. Kerim Bey
    Kerim Bey is a charismatic and resourceful MI6 ally in the James Bond series, best known for assisting Bond in Istanbul in the film and novel "From Russia, with Love."
  • E. Melikgazi
    Melikgazi is a central district and municipality of the city of Kayseri in central Turkey, known as one of the province’s main urban and administrative hubs.
  • 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_69d6ab2eaeb881909f7914758f859413 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90393cfb08190b5b45d3e5e32fad3 completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f471f6afc48190856a0f7c486b28aa completed May 1, 2026, 9:27 a.m.
NEDg Description generation batch_69f47b7ac4048190ae09f18f1a90338f completed May 1, 2026, 10:07 a.m.
NED2 Entity disambiguation (via description) batch_69f47db91f38819092b7b5c5e2bb489b completed May 1, 2026, 10:17 a.m.
Created at: April 8, 2026, 9:46 p.m.