Triple

T24183246
Position Surface form Disambiguated ID Type / Status
Subject Teide broom E599481 entity
Predicate commonName P570 FINISHED
Object Retama del Teide
Retama del Teide is a shrub species endemic to the high slopes of Mount Teide in Tenerife, known for its dense white spring blossoms that withstand harsh volcanic and alpine conditions.
E1622247 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: Retama del Teide | Statement: [Teide broom, commonName, Retama del Teide]
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: Retama del Teide
Triple: [Teide broom, commonName, Retama del Teide]
Generated description
Retama del Teide is a shrub species endemic to the high slopes of Mount Teide in Tenerife, known for its dense white spring blossoms that withstand harsh volcanic and alpine conditions.

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_69e288cca05481908faeb1563711114a completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1e1d6cfc08190acb77be3783c21be completed April 29, 2026, 10:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fad44e7d4819097910b9e0852d584 completed May 22, 2026, 1:11 a.m.
NEDg Description generation batch_6a0faf296d1c81908f90b583b5a962e9 completed May 22, 2026, 1:19 a.m.
NED2 Entity disambiguation (via description) batch_6a0fb006f43481908b4a3f3b20b29da7 completed May 22, 2026, 1:23 a.m.
Created at: April 17, 2026, 11:34 p.m.