Triple

T4417959
Position Surface form Disambiguated ID Type / Status
Subject Drama (regional unit) E95022 entity
Predicate contains P35 FINISHED
Object Paranesti
Paranesti is a small town and municipality in northeastern Greece, known for its mountainous landscapes, forests, and proximity to the Nestos River.
 E437046 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: Paranesti | Statement: [Drama (regional unit), contains, Paranesti]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Paranesti
Context triple: [Drama (regional unit), contains, Paranesti]
  • A. Parachi
    Parachi is a lesser-known Eastern Iranian language spoken by a small community in parts of Afghanistan.
  • B. Parsenn
    Parsenn is a major ski and mountain sports area in the Swiss Alps, renowned for its extensive slopes and connection to the resort town of Davos.
  • C. Mora
    Mora is a town in central Sweden’s Dalarna region, known for its traditional Swedish culture, proximity to Lake Siljan, and as the finish line of the Vasaloppet cross-country ski race.
  • D. Mora
    Mora is a surname of Hungarian origin most notably borne by the German-Hungarian writer Terézia Mora.
  • E. Mora
    Mora is a municipality in Portugal known for its rural Alentejo landscapes, traditional villages, and proximity to the Montargil reservoir.
  • 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: Paranesti
Triple: [Drama (regional unit), contains, Paranesti]
Generated description
Paranesti is a small town and municipality in northeastern Greece, known for its mountainous landscapes, forests, and proximity to the Nestos River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Paranesti
Target entity description: Paranesti is a small town and municipality in northeastern Greece, known for its mountainous landscapes, forests, and proximity to the Nestos River.
  • A. Parachi
    Parachi is a lesser-known Eastern Iranian language spoken by a small community in parts of Afghanistan.
  • B. Parsenn
    Parsenn is a major ski and mountain sports area in the Swiss Alps, renowned for its extensive slopes and connection to the resort town of Davos.
  • C. Mora
    Mora is a town in central Sweden’s Dalarna region, known for its traditional Swedish culture, proximity to Lake Siljan, and as the finish line of the Vasaloppet cross-country ski race.
  • D. Mora
    Mora is a surname of Hungarian origin most notably borne by the German-Hungarian writer Terézia Mora.
  • E. Mora
    Mora is a municipality in Portugal known for its rural Alentejo landscapes, traditional villages, and proximity to the Montargil reservoir.
  • 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_69b3453a36908190b95a79a297ca083c completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3551d5d7481908528c2de0a6fda06 completed March 13, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69b5f61fa6d88190b98810b542835817 completed March 14, 2026, 11:58 p.m.
NEDg Description generation batch_69b5f68a994c8190a5b524a4db16b097 completed March 15, 2026, midnight
NED2 Entity disambiguation (via description) batch_69b5f6ece3b08190b880743e9fe4dbad completed March 15, 2026, 12:01 a.m.
Created at: March 12, 2026, 11:29 p.m.