Triple
T14426950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yersiniaceae |
E357720
|
entity |
| Predicate | includesGenus |
P1393
|
FINISHED |
| Object | Pectobacterium |
E930660
|
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: Pectobacterium | Statement: [Yersiniaceae, includesGenus, Pectobacterium]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pectobacterium Context triple: [Yersiniaceae, includesGenus, Pectobacterium]
-
A.
Pectobacterium
chosen
Pectobacterium is a genus of plant-pathogenic bacteria known for causing soft rot diseases in a wide range of crops by degrading plant cell walls.
-
B.
Erwinia
Erwinia is a genus of plant-pathogenic bacteria known for causing diseases such as fire blight in fruit trees and soft rot in various crops.
-
C.
Xanthomonas
Xanthomonas is a genus of Gram-negative bacteria known primarily for causing a wide range of plant diseases that affect important agricultural crops worldwide.
-
D.
Photorhabdus
Photorhabdus is a genus of bioluminescent, insect-pathogenic bacteria that live in symbiosis with nematodes and are used as biological control agents.
-
E.
Psychrobacter
Psychrobacter is a genus of cold-adapted, often psychrophilic bacteria commonly found in low-temperature environments such as polar regions, deep seas, and refrigerated foods.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d8279402a88190821ffa39ae15bccf |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de911398f08190be85bc0a8bef6b1b |
completed | April 14, 2026, 7:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd5bcfa1d88190b59cefd3e305f55f |
completed | May 8, 2026, 3:43 a.m. |
Created at: April 10, 2026, 1:18 a.m.