Triple
T37496548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Acinetobacter |
E931842
|
entity |
| Predicate | drugResistance |
P81151
|
FINISHED |
| Object | multidrug-resistant |
—
|
LITERAL 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: multidrug-resistant | Statement: [Acinetobacter, drugResistance, multidrug-resistant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drugResistance Context triple: [Acinetobacter, drugResistance, multidrug-resistant]
-
A.
drugSusceptibility
Indicates that one entity (typically a microorganism, cell, or condition) is vulnerable or responsive to the effects of a specified drug or therapeutic agent.
-
B.
isResistant
Indicates that an entity can withstand, oppose, or is not significantly affected by a specified force, influence, or agent.
-
C.
isBacteriaResistant
chosen
Indicates that a bacterium is not inhibited or killed by a particular antibiotic or antimicrobial treatment.
-
D.
pestResistance
Indicates that an entity has the ability to withstand, deter, or remain unaffected by damage or harm caused by pests.
-
E.
diseaseResistance
Indicates how effectively one entity can prevent, withstand, or recover from harmful effects caused by a particular disease or pathogen in relation to another.
- F. None of above.
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_69f76ec457a4819094eeb3aed9baac11 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba68077788190b311e027435fcf87 |
completed | May 6, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69fba34c65ac8190b298f0f00d1dcc0e |
completed | May 6, 2026, 8:23 p.m. |
Created at: May 3, 2026, 4:17 p.m.