Triple

T1546949
Position Surface form Disambiguated ID Type / Status
Subject East Frisia E32998 entity
Predicate contains P35 FINISHED
Object Leer
Leer is a historic town in northwestern Germany known for its maritime heritage and traditional East Frisian culture.
 E176336 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: Leer | Statement: [East Frisia, contains, Leer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Leer
Context triple: [East Frisia, contains, Leer]
  • A. La Lecture
    La Lecture is an early 20th-century painting by Pablo Picasso that depicts a contemplative female figure and reflects his evolving style during his transition from Cubism toward a more classical, figurative approach.
  • B. Reedus
    Reedus is the surname of American actor and model Norman Reedus, best known for his role as Daryl Dixon on the television series "The Walking Dead."
  • C. Liber
    Liber is an ancient Roman god associated with viticulture, fertility, and freedom, often identified with the Greek god Dionysus.
  • D. Lesse
    The Lesse is a scenic river in southern Belgium known for flowing through the Ardennes, its limestone caves, and popular kayaking routes.
  • E. Aa en Hunze
    Aa en Hunze is a rural municipality in the northeastern Netherlands known for its natural landscapes, historic villages, and prehistoric dolmens.
  • 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: Leer
Triple: [East Frisia, contains, Leer]
Generated description
Leer is a historic town in northwestern Germany known for its maritime heritage and traditional East Frisian culture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Leer
Target entity description: Leer is a historic town in northwestern Germany known for its maritime heritage and traditional East Frisian culture.
  • A. La Lecture
    La Lecture is an early 20th-century painting by Pablo Picasso that depicts a contemplative female figure and reflects his evolving style during his transition from Cubism toward a more classical, figurative approach.
  • B. Reedus
    Reedus is the surname of American actor and model Norman Reedus, best known for his role as Daryl Dixon on the television series "The Walking Dead."
  • C. Liber
    Liber is an ancient Roman god associated with viticulture, fertility, and freedom, often identified with the Greek god Dionysus.
  • D. Lesse
    The Lesse is a scenic river in southern Belgium known for flowing through the Ardennes, its limestone caves, and popular kayaking routes.
  • E. Aa en Hunze
    Aa en Hunze is a rural municipality in the northeastern Netherlands known for its natural landscapes, historic villages, and prehistoric dolmens.
  • 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_69a885ee6db8819099502bc5ce8af881 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abb20dd5a88190b3d6e6f0004fe9b4 completed March 7, 2026, 5:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad30a073bc8190a269cb036775dfe4 completed March 8, 2026, 8:17 a.m.
NEDg Description generation batch_69ad3117b49881908916e7137f8b655c completed March 8, 2026, 8:19 a.m.
NED2 Entity disambiguation (via description) batch_69ad3179b0148190b69b16b5d2051ece completed March 8, 2026, 8:21 a.m.
Created at: March 4, 2026, 7:26 p.m.