Triple

T25319293
Position Surface form Disambiguated ID Type / Status
Subject Historic Centre of Porto E634833 entity
Predicate hasPart P35 FINISHED
Object Sé (Cathedral quarter)
Sé (Cathedral quarter) is the historic cathedral district of Porto, known for its medieval streets, landmark Porto Cathedral, and panoramic views over the city and Douro River.
E1676617 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: Sé (Cathedral quarter) | Statement: [Historic Centre of Porto, hasPart, Sé (Cathedral quarter)]
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: Sé (Cathedral quarter)
Triple: [Historic Centre of Porto, hasPart, Sé (Cathedral quarter)]
Generated description
Sé (Cathedral quarter) is the historic cathedral district of Porto, known for its medieval streets, landmark Porto Cathedral, and panoramic views over the city and Douro River.

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_69e75a9847c08190bb02990d06d5ffb7 completed April 21, 2026, 11:08 a.m.
NER Named-entity recognition batch_69f4968bc24c81909d8b9f0df2704210 completed May 1, 2026, 12:03 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1075e71d4c8190b0b404c7a0f749ab completed May 22, 2026, 3:27 p.m.
NEDg Description generation batch_6a10775af30c8190b81d59d29bf57a2e completed May 22, 2026, 3:33 p.m.
NED2 Entity disambiguation (via description) batch_6a1078eaf8888190b3453537d13d6cc5 completed May 22, 2026, 3:40 p.m.
Created at: April 21, 2026, 1:28 p.m.