Triple

T36131253
Position Surface form Disambiguated ID Type / Status
Subject Culemborg E1045020 entity
Predicate hasLandmark P105 FINISHED
Object Elisabeth Weeshuis (orphanage museum)
The Elisabeth Weeshuis (orphanage museum) is a historic former orphanage in Culemborg, the Netherlands, now serving as a museum that illustrates the history of orphan care and local heritage.
E2171102 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: Elisabeth Weeshuis (orphanage museum) | Statement: [Culemborg, hasLandmark, Elisabeth Weeshuis (orphanage museum)]
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: Elisabeth Weeshuis (orphanage museum)
Triple: [Culemborg, hasLandmark, Elisabeth Weeshuis (orphanage museum)]
Generated description
The Elisabeth Weeshuis (orphanage museum) is a historic former orphanage in Culemborg, the Netherlands, now serving as a museum that illustrates the history of orphan care and local heritage.

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_69f76e36a4508190b5bfc8f594272a4c completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b2fb575481908a40baeaee6bb410 completed May 3, 2026, 8:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38de14e91c8190915a0b71ea5f4c60 completed June 22, 2026, 7:02 a.m.
NEDg Description generation batch_6a3906773e808190a2fa8062e1003e86 completed June 22, 2026, 9:55 a.m.
NED2 Entity disambiguation (via description) batch_6a39080bd5c48190b55b38ebc2f1590c completed June 22, 2026, 10:01 a.m.
Created at: May 3, 2026, 4:08 p.m.