Triple

T24807603
Position Surface form Disambiguated ID Type / Status
Subject Melchior Cano E620695 entity
Predicate notableWork P4 FINISHED
Object De locis theologicis
De locis theologicis is a seminal 16th-century theological treatise by Melchior Cano that systematically analyzes the sources and methods of Catholic theology.
 E1650418 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: De locis theologicis | Statement: [Melchior Cano, notableWork, De locis theologicis]
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: De locis theologicis
Triple: [Melchior Cano, notableWork, De locis theologicis]
Generated description
De locis theologicis is a seminal 16th-century theological treatise by Melchior Cano that systematically analyzes the sources and methods of Catholic theology.

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_69e2fabf26bc8190b191faac8f67065b completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f42206efcc81908d4b512bd4ae899a completed May 1, 2026, 3:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a101c37fe6c8190a9b2ee6d9d31ef92 completed May 22, 2026, 9:04 a.m.
NEDg Description generation batch_6a102487faa48190964092d5dbfda45c completed May 22, 2026, 9:40 a.m.
NED2 Entity disambiguation (via description) batch_6a10251017548190b20095a68284d8ce completed May 22, 2026, 9:42 a.m.
Created at: April 18, 2026, 4:50 a.m.