Triple
T19916601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beinecke MS 408 |
E478680
|
entity |
| Predicate | pigments |
P109796
|
FINISHED |
| Object | various mineral and organic pigments |
—
|
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: various mineral and organic pigments | Statement: [Beinecke MS 408, pigments, various mineral and organic pigments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pigments Context triple: [Beinecke MS 408, pigments, various mineral and organic pigments]
-
A.
hasPigment
chosen
Indicates that one entity contains, incorporates, or is characterized by a particular pigment.
-
B.
primaryPigment
Indicates that one pigment is the main or dominant colorant used or present in relation to another entity.
-
C.
colors
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
-
D.
secondaryPigment
Indicates that one pigment functions as a secondary or supporting color relative to another primary pigment in a given context.
-
E.
usesDyes
Indicates that one entity employs or applies dyes in relation to another entity or process.
- 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_69d8e521855c8190b41871700afc8d6a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65994f4608190b79771ddea1040f5 |
completed | April 20, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69e537f070b481908958e0e5911dcdc1 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:53 p.m.