Triple
T25398780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Concord |
E636363
|
entity |
| Predicate | polyphenolContent |
P149614
|
FINISHED |
| Object | rich in polyphenols |
—
|
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: rich in polyphenols | Statement: [Concord, polyphenolContent, rich in polyphenols]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: polyphenolContent Context triple: [Concord, polyphenolContent, rich in polyphenols]
-
A.
tanninLevel
Indicates the degree or intensity of tannins present in or associated with something, typically a beverage like wine or tea.
-
B.
proteinContent
Indicates the amount or proportion of protein present in a given entity or substance.
-
C.
typicalPhenolLevel
chosen
Indicates that the phenol concentration or level falls within a normal or characteristic range for the given context.
-
D.
hasNutrientContent
Indicates that one entity contains or provides a specified amount or type of nutrient relative to another entity or standard.
-
E.
containsPulp
Indicates that one entity (typically a liquid or juice) includes solid or fibrous pulp within it.
- 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_69e75db263888190b77fff9e2827b9a2 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f584f8802c819085d55049bd94b075 |
completed | May 2, 2026, 5 a.m. |
| PD | Predicate disambiguation | batch_69f45d0dbc8c8190beecce679fce90a4 |
completed | May 1, 2026, 7:58 a.m. |
Created at: April 21, 2026, 1:50 p.m.