Triple

T28552095
Position Surface form Disambiguated ID Type / Status
Subject Zambujeira do Mar E722913 entity
Predicate hasBeach P1922 FINISHED
Object Praia do Carvalhal
Praia do Carvalhal is a scenic Atlantic beach on Portugal’s Alentejo coast, known for its rugged cliffs, natural setting, and proximity to the village of Zambujeira do Mar.
E1841422 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: Praia do Carvalhal | Statement: [Zambujeira do Mar, hasBeach, Praia do Carvalhal]
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: Praia do Carvalhal
Triple: [Zambujeira do Mar, hasBeach, Praia do Carvalhal]
Generated description
Praia do Carvalhal is a scenic Atlantic beach on Portugal’s Alentejo coast, known for its rugged cliffs, natural setting, and proximity to the village of Zambujeira do Mar.

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_69f01a60204481909af1bb76247b8221 completed April 28, 2026, 2:24 a.m.
NER Named-entity recognition batch_69f6504c5e1c8190903e5c4aeac37a30 completed May 2, 2026, 7:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24ec1d03e4819081ab7a432195e76b completed June 7, 2026, 3:57 a.m.
NEDg Description generation batch_6a24f04a62088190a7c7981e2baab162 completed June 7, 2026, 4:15 a.m.
NED2 Entity disambiguation (via description) batch_6a24f4b1f6bc8190b2edb78cc273e419 completed June 7, 2026, 4:33 a.m.
Created at: April 28, 2026, 3:43 a.m.