Triple

T25196687
Position Surface form Disambiguated ID Type / Status
Subject Israeli Children’s Museum E631018 entity
Predicate hasExhibition P1513 FINISHED
Object The Magic of Childhood
The Magic of Childhood is an interactive exhibition at the Israeli Children’s Museum that immerses young visitors in imaginative, play-based experiences exploring the wonders of growing up.
E1668729 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: The Magic of Childhood | Statement: [Israeli Children’s Museum, hasExhibition, The Magic of Childhood]
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: The Magic of Childhood
Triple: [Israeli Children’s Museum, hasExhibition, The Magic of Childhood]
Generated description
The Magic of Childhood is an interactive exhibition at the Israeli Children’s Museum that immerses young visitors in imaginative, play-based experiences exploring the wonders of growing up.

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_69e75a8b86c4819089eda22c843b739f completed April 21, 2026, 11:07 a.m.
NER Named-entity recognition batch_69f46e143e908190a3dff0f3a2399970 completed May 1, 2026, 9:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a105d2882788190824154d643158457 completed May 22, 2026, 1:42 p.m.
NEDg Description generation batch_6a105e17b4708190bceee2e6c3f4f3a7 completed May 22, 2026, 1:45 p.m.
NED2 Entity disambiguation (via description) batch_6a105fa381408190b9343fb060d29374 completed May 22, 2026, 1:52 p.m.
Created at: April 21, 2026, 12:50 p.m.