Triple
T15998020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bordeaux (See's Candies confection) |
E388022
|
entity |
| Predicate | hasFlavorComponent |
P104049
|
FINISHED |
| Object | brown sugar |
—
|
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: brown sugar | Statement: [Bordeaux (See's Candies confection), hasFlavorComponent, brown sugar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFlavorComponent Context triple: [Bordeaux (See's Candies confection), hasFlavorComponent, brown sugar]
-
A.
hasFlavorType
Indicates that an entity possesses or is characterized by a particular type or category of flavor.
-
B.
hasSecondaryFlavor
chosen
Indicates that an entity possesses an additional, subordinate flavor characteristic beyond its primary flavor.
-
C.
isOfficialFlavorOf
Indicates that one item is formally recognized or designated as an official flavor associated with another entity (such as a brand, product line, or event).
-
D.
hasQuarkFlavors
Indicates that an entity (such as a particle) possesses specific types (flavors) of quarks as its constituents.
-
E.
hasVarietyOfFlavors
Indicates that one entity offers or contains multiple distinct flavors or taste options.
- 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_69d86daa562c81908aacc179c0fe8fb5 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4e871c819082d7b1c1eaf5b4fe |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142d9d8e881909b559a3e3ca21d24 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:55 a.m.