Triple

T31754997
Position Surface form Disambiguated ID Type / Status
Subject Vlodrop E810532 entity
Predicate hasNearbyGermanLocality P197400 FINISHED
Object Effeld
Effeld is a small German village near the Dutch border, known for its rural character and proximity to the town of Vlodrop in the Netherlands.
 E1976197 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: Effeld | Statement: [Vlodrop, hasNearbyGermanLocality, Effeld]
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: Effeld
Triple: [Vlodrop, hasNearbyGermanLocality, Effeld]
Generated description
Effeld is a small German village near the Dutch border, known for its rural character and proximity to the town of Vlodrop in the Netherlands.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: hasNearbyGermanLocality
Context triple: [Vlodrop, hasNearbyGermanLocality, Effeld]
  • A. nearbySettlementGR chosen
    Indicates that one settlement is geographically located close to another settlement.
  • B. hasNearbyTown
    Indicates that one location has a town situated close to it in geographic proximity.
  • C. hasNearbyGeographicalArea
    Indicates that one geographical area is located in close spatial proximity to another geographical area.
  • D. federalStateCapitalNearby
    Indicates that the capital city of a federal state is geographically close to a specified reference location or entity.
  • E. hasMunicipalitySeatNearby
    Indicates that the municipality’s administrative seat is located in close proximity to the referenced place or entity.
  • 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_69f348e340d48190b780fae618c51464 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69ff136ed2a881908f713401083970d1 completed May 9, 2026, 10:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b948ac1d08190ae42c975a6e9a58c completed June 12, 2026, 5:09 a.m.
NEDg Description generation batch_6a2b96a258e08190878811121d63504c completed June 12, 2026, 5:18 a.m.
NED2 Entity disambiguation (via description) batch_6a2b9794d14081909374e7d0c582f4e0 completed June 12, 2026, 5:22 a.m.
PD Predicate disambiguation batch_69ff10f9e3448190b6cb6ea5a67713c1 completed May 9, 2026, 10:48 a.m.
Created at: April 30, 2026, 11:29 p.m.