Triple

T17133859
Position Surface form Disambiguated ID Type / Status
Subject Roman province of Dalmatia E415785 entity
Predicate includedIsland P970 FINISHED
Object Issa
Issa was an ancient Adriatic island settlement, known as a Greek colony and later Roman town off the coast of what is now Croatia.
 E1253035 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: Issa | Statement: [Roman province of Dalmatia, includedIsland, Issa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Issa
Context triple: [Roman province of Dalmatia, includedIsland, Issa]
  • A. Issa
    Issa is a masculine given name of Arabic origin commonly used in various Middle Eastern and Muslim-majority cultures.
  • B. Manguissa
    Manguissa is a Bantu language spoken by the Manguissa people in Cameroon.
  • C. Hasana
    Hasana is a small town in Egypt’s North Sinai Governorate, situated in the Sinai Peninsula.
  • D. Dyula
    Dyula is a Mande language widely used as a trade and lingua franca in parts of West Africa, particularly in Burkina Faso, Côte d’Ivoire, and Mali.
  • E. Kidira
    Kidira is a town in eastern Senegal near the Malian border that serves as an important road and rail crossing point between the two countries.
  • 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: Issa
Triple: [Roman province of Dalmatia, includedIsland, Issa]
Generated description
Issa was an ancient Adriatic island settlement, known as a Greek colony and later Roman town off the coast of what is now Croatia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Issa
Target entity description: Issa was an ancient Adriatic island settlement, known as a Greek colony and later Roman town off the coast of what is now Croatia.
  • A. Issa
    Issa is a masculine given name of Arabic origin commonly used in various Middle Eastern and Muslim-majority cultures.
  • B. Manguissa
    Manguissa is a Bantu language spoken by the Manguissa people in Cameroon.
  • C. Hasana
    Hasana is a small town in Egypt’s North Sinai Governorate, situated in the Sinai Peninsula.
  • D. Dyula
    Dyula is a Mande language widely used as a trade and lingua franca in parts of West Africa, particularly in Burkina Faso, Côte d’Ivoire, and Mali.
  • E. Kidira
    Kidira is a town in eastern Senegal near the Malian border that serves as an important road and rail crossing point between the two countries.
  • 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_69d886d15af4819092f92f8a129763e6 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f02cbb7881908aa69c3443d149d5 completed April 18, 2026, 8:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a01414eca3c8190aeec22fab3b5e767 completed May 11, 2026, 2:39 a.m.
NEDg Description generation batch_6a01423a771881908c2eaff14e335ee2 completed May 11, 2026, 2:43 a.m.
NED2 Entity disambiguation (via description) batch_6a01430b7e008190bc3366cc89564409 completed May 11, 2026, 2:46 a.m.
Created at: April 10, 2026, 5:36 a.m.