Triple

T29910230
Position Surface form Disambiguated ID Type / Status
Subject Second Alpujarras War E759661 entity
Predicate commander P1061 FINISHED
Object Marqués de Mondéjar
Marqués de Mondéjar was a prominent Spanish nobleman and military leader of the 16th century, noted for his role in suppressing uprisings in the Kingdom of Granada.
E1913465 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: Marqués de Mondéjar | Statement: [Second Alpujarras War, commander, Marqués de Mondéjar]
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: Marqués de Mondéjar
Triple: [Second Alpujarras War, commander, Marqués de Mondéjar]
Generated description
Marqués de Mondéjar was a prominent Spanish nobleman and military leader of the 16th century, noted for his role in suppressing uprisings in the Kingdom of Granada.

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_69f224600590819085e148a01c056ef6 completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f67759bd888190b1beb2fad6058b4d completed May 2, 2026, 10:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27891e5a54819080c29a14676defac completed June 9, 2026, 3:31 a.m.
NEDg Description generation batch_6a2789db54048190ab54d623ce1d4e2a completed June 9, 2026, 3:34 a.m.
NED2 Entity disambiguation (via description) batch_6a278a76f450819095acd3e2b23d2b73 completed June 9, 2026, 3:37 a.m.
Created at: April 29, 2026, 6:10 p.m.