Triple
T19590441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benedict's qualitative reagent for glucose |
E470215
|
entity |
| Predicate | greenColorIndicates |
P100027
|
FINISHED |
| Object | low concentration of reducing sugar |
—
|
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: low concentration of reducing sugar | Statement: [Benedict's qualitative reagent for glucose, greenColorIndicates, low concentration of reducing sugar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: greenColorIndicates Context triple: [Benedict's qualitative reagent for glucose, greenColorIndicates, low concentration of reducing sugar]
-
A.
greenUsedFor
Indicates that something green serves a particular purpose or function for something else.
-
B.
greenRepresents
Indicates that one entity uses the color green to symbolize, denote, or stand for another entity or concept.
-
C.
greenPrimary_x
Indicates that the subject has green as its primary or dominant color.
-
D.
greenPrimary_y
Indicates that the referenced entity serves as the primary or dominant green component in a color representation or relationship.
-
E.
colorIndicates
chosen
Indicates that a particular color serves as a sign, marker, or signal conveying specific information or status about something.
- 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_69d8e510024481908415c0d616fa6186 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e640552db48190b34555e4b72a75c4 |
completed | April 20, 2026, 3:03 p.m. |
| PD | Predicate disambiguation | batch_69e514dbdb988190b55931a8138c73e7 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:43 p.m.