Triple
T17039452
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caffeine-Free Coca-Cola |
E413406
|
entity |
| Predicate | keyDifference |
P74132
|
FINISHED |
| Object | does not contain caffeine |
—
|
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: does not contain caffeine | Statement: [Caffeine-Free Coca-Cola, keyDifference, does not contain caffeine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: keyDifference Context triple: [Caffeine-Free Coca-Cola, keyDifference, does not contain caffeine]
-
A.
differenceDescription
chosen
Indicates a textual explanation that characterizes how two entities differ from each other.
-
B.
keyFeature
Indicates that something is a primary, distinguishing, or most important feature of an entity.
-
C.
differIn
Indicates that two entities are not the same in at least one specified aspect, attribute, or value.
-
D.
keyObservation
Indicates that an entity is a primary or crucial observation about another entity, typically highlighting a central finding, feature, or insight.
-
E.
key
Indicates that one entity functions as a key (literal or metaphorical) that unlocks, enables access to, or provides a crucial solution or control over another entity.
- 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_69d886cd18288190b006abab23f811b7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d8f5844c819097eade4a2b42ab91 |
completed | April 18, 2026, 7:18 p.m. |
| PD | Predicate disambiguation | batch_69e35d60a588819084f53ef9f8b2e7c0 |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:33 a.m.