Triple

T27828016
Position Surface form Disambiguated ID Type / Status
Subject Church of St. Yur (St. George) E703009 entity
Predicate namedAfter P63 FINISHED
Object St. George
St. George is a Christian martyr and soldier-saint venerated across many traditions, most famously associated with the legend of slaying a dragon and symbolizing courage and faith.
E1794339 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: St. George | Statement: [Church of St. Yur (St. George), namedAfter, St. George]
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: St. George
Triple: [Church of St. Yur (St. George), namedAfter, St. George]
Generated description
St. George is a Christian martyr and soldier-saint venerated across many traditions, most famously associated with the legend of slaying a dragon and symbolizing courage and faith.

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_69ef840ad1e88190b5bff2d1ddec8700 completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f638988e588190862b1bdcbd9a483a completed May 2, 2026, 5:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a13034563a48190bfcb446035913e40 completed May 24, 2026, 1:55 p.m.
NEDg Description generation batch_6a13049071f88190863c9b0a59af8b70 completed May 24, 2026, 2 p.m.
NED2 Entity disambiguation (via description) batch_6a13055bbfc08190a2fd43a4d5708a43 completed May 24, 2026, 2:04 p.m.
Created at: April 27, 2026, 5:53 p.m.