Triple
T16290633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lledoner Pelut |
E395510
|
entity |
| Predicate | contributesToBlend |
P56866
|
FINISHED |
| Object | color |
—
|
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: color | Statement: [Lledoner Pelut, contributesToBlend, color]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contributesToBlend Context triple: [Lledoner Pelut, contributesToBlend, color]
-
A.
usedInBlends
chosen
Indicates that something serves as an ingredient or component within one or more mixtures, combinations, or blends.
-
B.
notableBlendStyle
Indicates a characteristic way in which elements are combined or mixed that is particularly distinctive or noteworthy.
-
C.
typicalBlendStyle
Indicates the usual or characteristic way in which two or more elements are combined or mixed together.
-
D.
contributeTo
Indicates that one entity provides support, resources, or effort that helps bring about, enhance, or maintain another entity, outcome, or state.
-
E.
hasBlendOfOldAndNew
Indicates that something combines or integrates both traditional/older elements and modern/newer elements into a single whole.
- 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_69d87f22c7248190a54c949738441e2e |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2491821d0819086cffdd7551ba85a |
completed | April 17, 2026, 2:52 p.m. |
| PD | Predicate disambiguation | batch_69e219f68d308190b71c1601303f0628 |
completed | April 17, 2026, 11:31 a.m. |
Created at: April 10, 2026, 5:05 a.m.