Triple

T15892777
Position Surface form Disambiguated ID Type / Status
Subject Bartın E385368 entity
Predicate hasPort P35 FINISHED
Object Amasra
Amasra is a historic coastal town and popular tourist destination on Turkey’s Black Sea coast, known for its scenic harbor, beaches, and ancient fortifications.
 E1182737 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: Amasra | Statement: [Bartın, hasPort, Amasra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Amasra
Context triple: [Bartın, hasPort, Amasra]
  • A. Navigo
    Navigo is the contactless smart card ticketing system used for public transportation across the Île-de-France region, including Paris.
  • B. Miaoulis
    Miaoulis is a Greek surname most famously associated with Admiral Andreas Miaoulis, a key naval leader in the Greek War of Independence.
  • C. Arsacia
    Arsacia is an alternative name historically used for the city of Rayy (near modern-day Tehran) in ancient Persia.
  • D. Galeata
    Galeata is a small historic town in Italy’s Emilia-Romagna region, known for its Roman and medieval heritage in the Apennine foothills.
  • E. Maleva
    Maleva is the wise Romani woman and mother of the original Wolf Man who serves as a mystical guide and bearer of the werewolf curse’s lore in Universal’s classic horror films.
  • 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: Amasra
Triple: [Bartın, hasPort, Amasra]
Generated description
Amasra is a historic coastal town and popular tourist destination on Turkey’s Black Sea coast, known for its scenic harbor, beaches, and ancient fortifications.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Amasra
Target entity description: Amasra is a historic coastal town and popular tourist destination on Turkey’s Black Sea coast, known for its scenic harbor, beaches, and ancient fortifications.
  • A. Navigo
    Navigo is the contactless smart card ticketing system used for public transportation across the Île-de-France region, including Paris.
  • B. Miaoulis
    Miaoulis is a Greek surname most famously associated with Admiral Andreas Miaoulis, a key naval leader in the Greek War of Independence.
  • C. Arsacia
    Arsacia is an alternative name historically used for the city of Rayy (near modern-day Tehran) in ancient Persia.
  • D. Galeata
    Galeata is a small historic town in Italy’s Emilia-Romagna region, known for its Roman and medieval heritage in the Apennine foothills.
  • E. Maleva
    Maleva is the wise Romani woman and mother of the original Wolf Man who serves as a mystical guide and bearer of the werewolf curse’s lore in Universal’s classic horror films.
  • 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_69d86da5b800819083a31be937d738b0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1563727cc819086b5c18b655dd7f6 completed April 16, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb0497cb481908e8ea4ebb9c4039d completed May 9, 2026, 10:08 p.m.
NEDg Description generation batch_69ffb1b0ac6481908d2e6106c0984d21 completed May 9, 2026, 10:14 p.m.
NED2 Entity disambiguation (via description) batch_69ffb2461ea48190ba05f7da71b0f80f completed May 9, 2026, 10:16 p.m.
Created at: April 10, 2026, 4:51 a.m.