Triple
T25876380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Modica chocolate |
E651912
|
entity |
| Predicate | industrialEmulsifiers |
P56320
|
FINISHED |
| Object | traditionally absent |
—
|
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: traditionally absent | Statement: [Modica chocolate, industrialEmulsifiers, traditionally absent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: industrialEmulsifiers Context triple: [Modica chocolate, industrialEmulsifiers, traditionally absent]
-
A.
industrialCategory
Indicates the industry or sector classification to which an entity (such as a business or organization) belongs.
-
B.
industrialFocus
Indicates a relationship where an entity is primarily concerned with, specialized in, or directed toward a particular industrial sector or area of industrial activity.
-
C.
containsAdditives
chosen
Indicates that one entity includes or is composed of additional substances or ingredients beyond its primary or original components.
-
D.
ingredientType
Indicates that one entity is classified as a specific type or category of ingredient in relation to another.
-
E.
oilContent
Indicates the amount or proportion of oil present in a given substance, material, or item.
- 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_69e7ab3ad9d88190841ddcb93ab02e96 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f60c698ae48190871cd445422bad91 |
completed | May 2, 2026, 2:38 p.m. |
| PD | Predicate disambiguation | batch_69f60b874cc88190a487230abb69efea |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 22, 2026, 8:12 a.m.