Triple

T31764358
Position Surface form Disambiguated ID Type / Status
Subject Siege of Collioure (1794) E810766 entity
Predicate commander P1061 FINISHED
Object Eugenio Navarro
Eugenio Navarro was a Spanish military commander active during the French Revolutionary Wars, notably involved in operations in the eastern Pyrenees.
E2013363 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: Eugenio Navarro | Statement: [Siege of Collioure (1794), commander, Eugenio Navarro]
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: Eugenio Navarro
Triple: [Siege of Collioure (1794), commander, Eugenio Navarro]
Generated description
Eugenio Navarro was a Spanish military commander active during the French Revolutionary Wars, notably involved in operations in the eastern Pyrenees.

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_69f348e463e08190b902d4819195e1f0 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6abaa1f648190b77073771df3bf3b completed May 3, 2026, 1:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a347b61fb448190a23ab0cd418bf7b2 completed June 18, 2026, 11:12 p.m.
NEDg Description generation batch_6a347cf75eb88190a13b4efd38698b4b completed June 18, 2026, 11:19 p.m.
NED2 Entity disambiguation (via description) batch_6a347e5172008190a0672bfb37c7326c completed June 18, 2026, 11:25 p.m.
Created at: April 30, 2026, 11:31 p.m.