Triple

T31760059
Position Surface form Disambiguated ID Type / Status
Subject Montgrí Massif E810655 entity
Predicate hasViewOver P1323 FINISHED
Object Empordà plain
The Empordà plain is a broad coastal lowland in northeastern Catalonia, Spain, known for its agricultural landscapes, wetlands, and views toward the Mediterranean Sea.
 E1975645 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: Empordà plain | Statement: [Montgrí Massif, hasViewOver, Empordà plain]
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: Empordà plain
Triple: [Montgrí Massif, hasViewOver, Empordà plain]
Generated description
The Empordà plain is a broad coastal lowland in northeastern Catalonia, Spain, known for its agricultural landscapes, wetlands, and views toward the Mediterranean Sea.

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_69f348e340d48190b780fae618c51464 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6ab7f9fdc8190a3dd5ddbaf2927d3 completed May 3, 2026, 1:57 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b948ee8c08190a2860ec7279369e3 completed June 12, 2026, 5:09 a.m.
NEDg Description generation batch_6a2b958e9ebc81909225029c40526808 completed June 12, 2026, 5:13 a.m.
NED2 Entity disambiguation (via description) batch_6a2b961cb34081909831c49b6c0ae48f completed June 12, 2026, 5:16 a.m.
Created at: April 30, 2026, 11:30 p.m.