Triple
T6075466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penicillium chrysogenum |
E135388
|
entity |
| Predicate | colonyColor |
P68504
|
FINISHED |
| Object | blue-green |
—
|
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: blue-green | Statement: [Penicillium chrysogenum, colonyColor, blue-green]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colonyColor Context triple: [Penicillium chrysogenum, colonyColor, blue-green]
-
A.
colonyType
Indicates the specific classification or kind of colony associated with an entity (e.g., its organizational or structural type).
-
B.
colonyStatus
Indicates the political or administrative condition of a territory in relation to a colonizing power, such as whether it is a colony, former colony, or non-colonial.
-
C.
colonySize
Indicates the number of individuals or units that make up a colony in the described context.
-
D.
colonyName
Indicates that a colony entity is associated with and identified by a specific name.
-
E.
colonyOf
Indicates that one entity is a colony belonging to, founded by, or politically dependent on another entity.
- F. None of above. chosen
Provenance (4 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_69c0087ad31c8190ab936e0ff28614b6 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0575ec63081908a868a41855acf73 |
completed | March 22, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69c049f21fe08190995df3c5c05fb8ea |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04e8d4a148190bd8f95caae978e1b |
completed | March 22, 2026, 8:18 p.m. |
Created at: March 22, 2026, 4:11 p.m.