Triple

T37763013
Position Surface form Disambiguated ID Type / Status
Subject Fruela II of León E941333 entity
Predicate child P120 FINISHED
Object Alfonso Froilaz
Alfonso Froilaz was a short-lived early 10th-century claimant to the thrones of León and Galicia, involved in the dynastic struggles that followed the death of his father, King Fruela II.
E2283479 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: Alfonso Froilaz | Statement: [Fruela II of León, child, Alfonso Froilaz]
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: Alfonso Froilaz
Triple: [Fruela II of León, child, Alfonso Froilaz]
Generated description
Alfonso Froilaz was a short-lived early 10th-century claimant to the thrones of León and Galicia, involved in the dynastic struggles that followed the death of his father, King Fruela II.

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_69f76ee3251881909bb4451aad50752b completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fbaf18085481908c774e8f8bbb9a41 completed May 6, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4256cbfdc08190bde47ef92a78408f completed June 29, 2026, 11:28 a.m.
NEDg Description generation batch_6a4257493dd88190acfb9bd77c935268 completed June 29, 2026, 11:30 a.m.
NED2 Entity disambiguation (via description) batch_6a42579e40e48190bc4c52ebb6510266 completed June 29, 2026, 11:31 a.m.
Created at: May 3, 2026, 4:19 p.m.