Triple

T32500185
Position Surface form Disambiguated ID Type / Status
Subject Northern Luxembourg E830634 entity
Predicate hasAttraction P105 FINISHED
Object Clervaux Castle
Clervaux Castle is a restored medieval fortress in the town of Clervaux, Luxembourg, known for housing the famous "The Family of Man" photography exhibition and local history museums.
E2010329 NE FINISHED

How this triple was built (2 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: Clervaux Castle | Statement: [Northern Luxembourg, hasAttraction, Clervaux Castle]
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: Clervaux Castle
Triple: [Northern Luxembourg, hasAttraction, Clervaux Castle]
Generated description
Clervaux Castle is a restored medieval fortress in the town of Clervaux, Luxembourg, known for housing the famous "The Family of Man" photography exhibition and local history museums.

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_69f349219cb8819087e120f509629c1b completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c442b4d88190a00e9781206b0520 completed May 3, 2026, 3:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a347058807881908b47c8eb8840d4c1 completed June 18, 2026, 10:25 p.m.
NEDg Description generation batch_6a3471e541888190b41a9562c7d29278 completed June 18, 2026, 10:32 p.m.
NED2 Entity disambiguation (via description) batch_6a347293cdf08190bbc8ce521ded677c completed June 18, 2026, 10:34 p.m.
Created at: May 1, 2026, 12:59 a.m.