Triple

T14667103
Position Surface form Disambiguated ID Type / Status
Subject Central Province E344406 entity
Predicate hasTown P847 FINISHED
Object Serenje
Serenje is a town in Zambia that serves as an important administrative and transport hub within the country’s Central Province.
 E1112884 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: Serenje | Statement: [Central Province, hasTown, Serenje]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Serenje
Context triple: [Central Province, hasTown, Serenje]
  • A. Nydri
    Nydri is a popular coastal village and tourist resort on the Greek island of Lefkada, known for its scenic harbor, nearby islets, and vibrant waterfront.
  • B. Sedova
    Sedova is a Russian surname most notably associated with revolutionary figure Natalia Sedova, the second wife of Leon Trotsky.
  • C. Slunj
    Slunj is a small historic town in central Croatia known for its picturesque waterfalls and riverside mills, particularly in the Rastoke area.
  • D. Povljana
    Povljana is a coastal municipality and tourist settlement on the island of Pag in Croatia, known for its beaches and Mediterranean landscape.
  • E. Sutsilvan
    Sutsilvan is a traditional variety of the Romansh language historically spoken in parts of the Swiss canton of Graubünden.
  • 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: Serenje
Triple: [Central Province, hasTown, Serenje]
Generated description
Serenje is a town in Zambia that serves as an important administrative and transport hub within the country’s Central Province.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Serenje
Target entity description: Serenje is a town in Zambia that serves as an important administrative and transport hub within the country’s Central Province.
  • A. Nydri
    Nydri is a popular coastal village and tourist resort on the Greek island of Lefkada, known for its scenic harbor, nearby islets, and vibrant waterfront.
  • B. Sedova
    Sedova is a Russian surname most notably associated with revolutionary figure Natalia Sedova, the second wife of Leon Trotsky.
  • C. Slunj
    Slunj is a small historic town in central Croatia known for its picturesque waterfalls and riverside mills, particularly in the Rastoke area.
  • D. Povljana
    Povljana is a coastal municipality and tourist settlement on the island of Pag in Croatia, known for its beaches and Mediterranean landscape.
  • E. Sutsilvan
    Sutsilvan is a traditional variety of the Romansh language historically spoken in parts of the Swiss canton of Graubünden.
  • 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_69d822e283fc8190a0e4c235cf880052 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb54dda1c8190bf16d17e26a2bba6 completed April 14, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdd5e63e6c8190ba67776719f2ff0c completed May 8, 2026, 12:24 p.m.
NEDg Description generation batch_69fdda3510bc8190b12783ded11b5796 completed May 8, 2026, 12:42 p.m.
NED2 Entity disambiguation (via description) batch_69fddaa56f4c8190ba56af6a7a56a201 completed May 8, 2026, 12:44 p.m.
Created at: April 10, 2026, 1:27 a.m.