Triple

T24053325
Position Surface form Disambiguated ID Type / Status
Subject Phyllachoraceae E595722 entity
Predicate includes P1393 FINISHED
Object Phyllachora
Phyllachora is a genus of parasitic ascomycete fungi known for forming dark tar-like spots on the leaves of various plants.
E1625238 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: Phyllachora | Statement: [Phyllachoraceae, includes, Phyllachora]
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: Phyllachora
Triple: [Phyllachoraceae, includes, Phyllachora]
Generated description
Phyllachora is a genus of parasitic ascomycete fungi known for forming dark tar-like spots on the leaves of various plants.

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_69e288c184b081909f1f1751fb8e299a completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1d9d4325c819080b878fe77280947 completed April 29, 2026, 10:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fbcfa05f081909f9102c31c21a8fb completed May 22, 2026, 2:18 a.m.
NEDg Description generation batch_6a0fc03e594c8190aad5eed4e6006ffc completed May 22, 2026, 2:32 a.m.
NED2 Entity disambiguation (via description) batch_6a0fc15d85ec8190841005d247ad01f3 completed May 22, 2026, 2:37 a.m.
Created at: April 17, 2026, 10:21 p.m.