Triple

T25623575
Position Surface form Disambiguated ID Type / Status
Subject Wilsede E642365 entity
Predicate nearestRoadAccessPoints P32540 FINISHED
Object Niederhaverbeck
Niederhaverbeck is a small settlement in the Lüneburg Heath region of Lower Saxony, Germany, serving as a key access point for visitors to the nearby nature and hiking areas around Wilsede.
 E1688467 NE FINISHED

How this triple was built (3 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: Niederhaverbeck | Statement: [Wilsede, nearestRoadAccessPoints, Niederhaverbeck]
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: Niederhaverbeck
Triple: [Wilsede, nearestRoadAccessPoints, Niederhaverbeck]
Generated description
Niederhaverbeck is a small settlement in the Lüneburg Heath region of Lower Saxony, Germany, serving as a key access point for visitors to the nearby nature and hiking areas around Wilsede.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: nearestRoadAccessPoints
Context triple: [Wilsede, nearestRoadAccessPoints, Niederhaverbeck]
  • A. nearestRoadHead chosen
    Indicates that one location is the closest accessible road endpoint (or road access point) to another location.
  • B. infrastructureNearby
    Indicates that one entity is located close to another entity that serves as infrastructure (such as roads, utilities, or public facilities).
  • C. nearbyMajorRoad
    Indicates that one entity is located close to a significant or heavily used road.
  • D. transportationNearby
    Indicates that there is a transportation facility or service located close to the referenced entity.
  • E. distanceFromRoads
    Indicates the measured or estimated spatial distance between a location and the nearest road.
  • F. None of above.

Provenance (6 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_69e77e7a96748190b10f2699041e4e43 completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f6135293908190809e255bf6334760 completed May 2, 2026, 3:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10b780d5e08190aed14ce5a30cb237 completed May 22, 2026, 8:07 p.m.
NEDg Description generation batch_6a10b94377108190a5fb35e99b5f0351 completed May 22, 2026, 8:14 p.m.
NED2 Entity disambiguation (via description) batch_6a10b9c6dbf48190abe4efb4035db2a0 completed May 22, 2026, 8:17 p.m.
PD Predicate disambiguation batch_69f611a72780819082f44e66ca2c6ac9 completed May 2, 2026, 3 p.m.
Created at: April 21, 2026, 5:06 p.m.