Triple
T20878478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Three-Course Dinner Chewing Gum |
E514082
|
entity |
| Predicate | hasFlavorSequence |
P142217
|
FINISHED |
| Object | tomato soup |
—
|
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: tomato soup | Statement: [Three-Course Dinner Chewing Gum, hasFlavorSequence, tomato soup]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFlavorSequence Context triple: [Three-Course Dinner Chewing Gum, hasFlavorSequence, tomato soup]
-
A.
hasFlavorType
Indicates that an entity possesses or is characterized by a particular type or category of flavor.
-
B.
hasSecondaryFlavor
Indicates that an entity possesses an additional, subordinate flavor characteristic beyond its primary flavor.
-
C.
isFlavored
Indicates that one entity imparts a particular taste or flavor characteristic to another entity.
-
D.
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).
-
E.
hasVarietyOfFlavors
Indicates that one entity offers or contains multiple distinct flavors or taste options.
- 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_69e0b4f733f081908a401c0b7beb0b9f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c6775f108190a79cd5e8c31cecf6 |
completed | April 21, 2026, 12:36 a.m. |
| PD | Predicate disambiguation | batch_69e5c9a8dc148190b33ff51894e2a8f9 |
completed | April 20, 2026, 6:37 a.m. |
| PDg | Predicate description generation | batch_69e5d53c4d6881909b4d0a716fa5ed4a |
completed | April 20, 2026, 7:26 a.m. |
Created at: April 16, 2026, 12:45 p.m.