Triple
T38560820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Listeria |
E928071
|
entity |
| Predicate | hemolysis |
P185916
|
FINISHED |
| Object | some species are beta-hemolytic |
—
|
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: some species are beta-hemolytic | Statement: [Listeria, hemolysis, some species are beta-hemolytic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hemolysis Context triple: [Listeria, hemolysis, some species are beta-hemolytic]
-
A.
hemolysisType
chosen
Indicates the specific kind or pattern of hemolysis occurring or observed in a given context.
-
B.
hasBloodPigment
Indicates that an organism possesses a specific pigment in its blood responsible for coloration and often for oxygen transport.
-
C.
bloodStatus
Indicates the classification of an entity based on the type or purity of its blood or lineage.
-
D.
hasBlood
Indicates that one entity possesses or contains the blood of another entity.
-
E.
bloodTrait
Indicates that one entity has a specific blood-related characteristic, property, or attribute associated with another entity.
- 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_69f76eb8d1808190a588af29d8b266d6 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdfbc71c481908ba7f87907b17782 |
completed | May 7, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe580b8819087f143596b2c79c0 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 3, 2026, 4:32 p.m.