Triple

T392272
Position Surface form Disambiguated ID Type / Status
Subject Groningen E8905 entity
Predicate contains P35 FINISHED
Object Pekela
Pekela is a municipality in the province of Groningen in the northeastern Netherlands, known for its rural character and historical peat colonies.
 E51701 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: Pekela | Statement: [Groningen, contains, Pekela]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Pekela
Context triple: [Groningen, contains, Pekela]
  • A. Muscovy
    Muscovy was a late medieval and early modern Russian principality centered on Moscow that expanded to form the core of the Russian state.
  • B. Rana
    Rana was the hereditary royal title borne by the ruling dynasty of the former princely state of Porbandar in western India.
  • C. Beaver
    Beaver was one of the British ships in Boston Harbor whose tea cargo was destroyed during the Boston Tea Party protest in 1773.
  • D. Canino
    Canino is a small town in the Lazio region of central Italy, historically notable as the birthplace of Pope Paul III.
  • E. Rednitz
    The Rednitz is a river in Bavaria, Germany, that flows through cities such as Fürth and joins with the Pegnitz to form the Regnitz.
  • 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: Pekela
Triple: [Groningen, contains, Pekela]
Generated description
Pekela is a municipality in the province of Groningen in the northeastern Netherlands, known for its rural character and historical peat colonies.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Pekela
Target entity description: Pekela is a municipality in the province of Groningen in the northeastern Netherlands, known for its rural character and historical peat colonies.
  • A. Muscovy
    Muscovy was a late medieval and early modern Russian principality centered on Moscow that expanded to form the core of the Russian state.
  • B. Rana
    Rana was the hereditary royal title borne by the ruling dynasty of the former princely state of Porbandar in western India.
  • C. Beaver
    Beaver was one of the British ships in Boston Harbor whose tea cargo was destroyed during the Boston Tea Party protest in 1773.
  • D. Canino
    Canino is a small town in the Lazio region of central Italy, historically notable as the birthplace of Pope Paul III.
  • E. Rednitz
    The Rednitz is a river in Bavaria, Germany, that flows through cities such as Fürth and joins with the Pegnitz to form the Regnitz.
  • 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_69a2e7f55c60819097aff65ea2ca2832 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ec7492288190bf33c9c869a0710f completed Feb. 28, 2026, 1:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69a41772e19c8190b02a212f13b4d8aa completed March 1, 2026, 10:39 a.m.
NEDg Description generation batch_69a417d8d8ac8190b9e36238b7bd9132 completed March 1, 2026, 10:41 a.m.
NED2 Entity disambiguation (via description) batch_69a4184c1b1c8190b728a2ef5cdc8346 completed March 1, 2026, 10:43 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.