Triple

T30000012
Position Surface form Disambiguated ID Type / Status
Subject District of Guarda E762140 entity
Predicate hasMunicipality P847 FINISHED
Object Guarda Municipality
Guarda Municipality is an administrative division in central Portugal that includes the historic city of Guarda, known as the country’s highest city and a regional cultural and economic center.
E1893916 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: Guarda Municipality | Statement: [District of Guarda, hasMunicipality, Guarda Municipality]
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: Guarda Municipality
Triple: [District of Guarda, hasMunicipality, Guarda Municipality]
Generated description
Guarda Municipality is an administrative division in central Portugal that includes the historic city of Guarda, known as the country’s highest city and a regional cultural and economic center.

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_69f2246a47ac81909cf5213053687ffc completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f6794da2cc8190af2afa95c616305a completed May 2, 2026, 10:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a272209664481909830cfed0aee69fa completed June 8, 2026, 8:11 p.m.
NEDg Description generation batch_6a272333f384819084456b384bc17a6c completed June 8, 2026, 8:16 p.m.
NED2 Entity disambiguation (via description) batch_6a2723e303108190a1e6d1965b21a8e8 completed June 8, 2026, 8:19 p.m.
Created at: April 29, 2026, 6:41 p.m.