Triple

T36941780
Position Surface form Disambiguated ID Type / Status
Subject Teodora Alonso Realonda E913786 entity
Predicate father P120 FINISHED
Object Lorenzo Alonso
Lorenzo Alonso was a 19th-century Filipino mestizo from a prominent family, best known as the husband of Teodora Alonso and the maternal grandfather of national hero José Rizal.
E2204760 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: Lorenzo Alonso | Statement: [Teodora Alonso Realonda, father, Lorenzo Alonso]
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: Lorenzo Alonso
Triple: [Teodora Alonso Realonda, father, Lorenzo Alonso]
Generated description
Lorenzo Alonso was a 19th-century Filipino mestizo from a prominent family, best known as the husband of Teodora Alonso and the maternal grandfather of national hero José Rizal.

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_69f76e8a6a5c81909c1febf32bf3fe23 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f9fed250848190965117d3b26c0e5a completed May 5, 2026, 2:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3e164344e08190931b37f6982d78ff completed June 26, 2026, 6:03 a.m.
NEDg Description generation batch_6a3e16c86a84819085a695e70971c83b completed June 26, 2026, 6:06 a.m.
NED2 Entity disambiguation (via description) batch_6a3e1de0bf6c819085b7d2ac2759776c completed June 26, 2026, 6:36 a.m.
Created at: May 3, 2026, 4:13 p.m.