Triple

T29049143
Position Surface form Disambiguated ID Type / Status
Subject Castro de Avelãs E735216 entity
Predicate contains P35 FINISHED
Object Castro de Avelãs Monastery
Castro de Avelãs Monastery is a historic medieval monastic complex in northeastern Portugal, noted for its distinctive Romanesque architecture and cultural significance.
E1846691 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: Castro de Avelãs Monastery | Statement: [Castro de Avelãs, contains, Castro de Avelãs Monastery]
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: Castro de Avelãs Monastery
Triple: [Castro de Avelãs, contains, Castro de Avelãs Monastery]
Generated description
Castro de Avelãs Monastery is a historic medieval monastic complex in northeastern Portugal, noted for its distinctive Romanesque architecture and cultural significance.

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_69f077e64b88819094d37bdbca8191b3 completed April 28, 2026, 9:03 a.m.
NER Named-entity recognition batch_69f66063cc04819098c27a663055d3d8 completed May 2, 2026, 8:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a251f75b2908190b3d7cad0f81e4f76 completed June 7, 2026, 7:36 a.m.
NEDg Description generation batch_6a2524587f4c8190866c4b0e6e8cf43a completed June 7, 2026, 7:57 a.m.
NED2 Entity disambiguation (via description) batch_6a2524b966888190a20408ad0f27f892 completed June 7, 2026, 7:58 a.m.
Created at: April 28, 2026, 10:07 a.m.