Triple

T25329208
Position Surface form Disambiguated ID Type / Status
Subject Province of Zamora E635102 entity
Predicate highestPoint P210 FINISHED
Object Peña Trevinca
Peña Trevinca is a prominent mountain peak in northwestern Spain, known for being the highest summit in the Trevinca massif on the border between Galicia and Castile and León.
E1706028 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: Peña Trevinca | Statement: [Province of Zamora, highestPoint, Peña Trevinca]
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: Peña Trevinca
Triple: [Province of Zamora, highestPoint, Peña Trevinca]
Generated description
Peña Trevinca is a prominent mountain peak in northwestern Spain, known for being the highest summit in the Trevinca massif on the border between Galicia and Castile and León.

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_69e75a9908108190a95427a97020632a completed April 21, 2026, 11:08 a.m.
NER Named-entity recognition batch_69f497c2c7b081909a09153061b01fa7 completed May 1, 2026, 12:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1107464e5c8190a01a1410b8ebb03d completed May 23, 2026, 1:47 a.m.
NEDg Description generation batch_6a110a36deec8190b0e6ded2dc4c41ea completed May 23, 2026, 2 a.m.
NED2 Entity disambiguation (via description) batch_6a110a9b301081908576c1f79b334544 completed May 23, 2026, 2:02 a.m.
Created at: April 21, 2026, 1:30 p.m.