Triple

T35117243
Position Surface form Disambiguated ID Type / Status
Subject Alzatea E1013474 entity
Predicate namedBy P63 FINISHED
Object Hipólito Ruiz López
Hipólito Ruiz López was an 18th-century Spanish botanist best known for his extensive botanical explorations in Peru and Chile and for describing numerous new plant genera and species.
E2130868 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: Hipólito Ruiz López | Statement: [Alzatea, namedBy, Hipólito Ruiz López]
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: Hipólito Ruiz López
Triple: [Alzatea, namedBy, Hipólito Ruiz López]
Generated description
Hipólito Ruiz López was an 18th-century Spanish botanist best known for his extensive botanical explorations in Peru and Chile and for describing numerous new plant genera and species.

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_69f76dd659d08190bcdc00d37caafb62 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78c39ce4481909fda117c1b6296fe completed May 3, 2026, 5:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3803f6ff7c81908b9ae3e4b59c6c38 completed June 21, 2026, 3:32 p.m.
NEDg Description generation batch_6a3804672aa481909e0fab282f6d7a51 completed June 21, 2026, 3:33 p.m.
NED2 Entity disambiguation (via description) batch_6a38051421208190a195f5eef3667f47 completed June 21, 2026, 3:36 p.m.
Created at: May 3, 2026, 4:01 p.m.