Triple
T24815455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aztec codices |
E620907
|
entity |
| Predicate | colorUse |
P157743
|
FINISHED |
| Object | vegetal 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: vegetal pigments | Statement: [Aztec codices, colorUse, vegetal pigments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colorUse Context triple: [Aztec codices, colorUse, vegetal pigments]
-
A.
colors
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
-
B.
colorOftenUsed
Indicates that a particular color is frequently used or commonly applied in relation to something.
-
C.
colorIndicates
Indicates that a particular color serves as a sign, marker, or signal conveying specific information or status about something.
-
D.
colorInfluence
Indicates how the presence or use of one color affects the perception, appearance, or impact of another.
-
E.
colorTincture
Indicates that one entity has a specific heraldic color or tincture applied to it.
- 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_69e2fabfd4648190bd0e5c7f4dbb6cab |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f44a417a58819081777e18dda149fd |
completed | May 1, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69f442b8479c8190a7c8e416ac9e28a0 |
completed | May 1, 2026, 6:05 a.m. |
| PDg | Predicate description generation | batch_69f44a3adb7c8190941572f718b3b93c |
completed | May 1, 2026, 6:37 a.m. |
Created at: April 18, 2026, 5:02 a.m.