Triple

T37449919
Position Surface form Disambiguated ID Type / Status
Subject Pseudomonas E930646 entity
Predicate notableSpecies P965 FINISHED
Object Pseudomonas mendocina
Pseudomonas mendocina is a Gram-negative, rod-shaped soil bacterium known for its metabolic versatility and ability to degrade various environmental pollutants.
E2232034 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: Pseudomonas mendocina | Statement: [Pseudomonas, notableSpecies, Pseudomonas mendocina]
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: Pseudomonas mendocina
Triple: [Pseudomonas, notableSpecies, Pseudomonas mendocina]
Generated description
Pseudomonas mendocina is a Gram-negative, rod-shaped soil bacterium known for its metabolic versatility and ability to degrade various environmental pollutants.

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_69f76ec0b9488190b7a4fae632bd1d2f completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb8e07ff6c8190834fa71fa25675e0 completed May 6, 2026, 6:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a409ef570d08190a937a23dab2b04b1 completed June 28, 2026, 4:11 a.m.
NEDg Description generation batch_6a409ffd39648190b86e65c728810f62 completed June 28, 2026, 4:15 a.m.
NED2 Entity disambiguation (via description) batch_6a40a0c329908190acbd2d3cc33d29fc completed June 28, 2026, 4:19 a.m.
Created at: May 3, 2026, 4:17 p.m.