Triple

T4430110
Position Surface form Disambiguated ID Type / Status
Subject Hillerød E95304 entity
Predicate hasNearbyForest P44059 FINISHED
Object Gribskov
Gribskov is one of Denmark’s largest and oldest forests, known for its diverse woodland landscapes, rich wildlife, and extensive network of walking and cycling trails.
 E440920 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: Gribskov | Statement: [Hillerød, hasNearbyForest, Gribskov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gribskov
Context triple: [Hillerød, hasNearbyForest, Gribskov]
  • A. Zaslofsky
    Zaslofsky is a surname most notably associated with Max Zaslofsky, an early star guard in the National Basketball Association.
  • B. Bryc
    Bryc is an alternative spelling of the given name Bryce, typically used as a modern or stylistic variant.
  • C. Flemming
    Flemming is a surname and given name of Germanic origin, used by various notable individuals across fields such as politics, arts, and science.
  • D. Guralnik
    Guralnik is a surname most notably associated with American theoretical physicist Gerald Guralnik, a co-discoverer of the Higgs mechanism.
  • E. Blaustein
    Blaustein is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, situated near the city of Ulm.
  • 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: Gribskov
Triple: [Hillerød, hasNearbyForest, Gribskov]
Generated description
Gribskov is one of Denmark’s largest and oldest forests, known for its diverse woodland landscapes, rich wildlife, and extensive network of walking and cycling trails.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gribskov
Target entity description: Gribskov is one of Denmark’s largest and oldest forests, known for its diverse woodland landscapes, rich wildlife, and extensive network of walking and cycling trails.
  • A. Zaslofsky
    Zaslofsky is a surname most notably associated with Max Zaslofsky, an early star guard in the National Basketball Association.
  • B. Bryc
    Bryc is an alternative spelling of the given name Bryce, typically used as a modern or stylistic variant.
  • C. Flemming
    Flemming is a surname and given name of Germanic origin, used by various notable individuals across fields such as politics, arts, and science.
  • D. Guralnik
    Guralnik is a surname most notably associated with American theoretical physicist Gerald Guralnik, a co-discoverer of the Higgs mechanism.
  • E. Blaustein
    Blaustein is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, situated near the city of Ulm.
  • 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_69b3453c2a0c8190926b574c90766db9 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35569b3388190bdef2568f5dc04ce completed March 13, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69b6136caa248190a84423cede1908c3 completed March 15, 2026, 2:03 a.m.
NEDg Description generation batch_69b617c13d4481909d22d201ce405d3a completed March 15, 2026, 2:21 a.m.
NED2 Entity disambiguation (via description) batch_69b6187687f8819084e2d611e9e31f79 completed March 15, 2026, 2:24 a.m.
Created at: March 12, 2026, 11:30 p.m.