Triple
T31847017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ballantine beer can |
E812966
|
entity |
| Predicate | conditionAffects |
P125238
|
FINISHED |
| Object | collectible value |
—
|
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: collectible value | Statement: [Ballantine beer can, conditionAffects, collectible value]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conditionAffects Context triple: [Ballantine beer can, conditionAffects, collectible value]
-
A.
affectsPhenomenon
Indicates that one phenomenon produces an influence or change on another phenomenon.
-
B.
conditions
Indicates that one entity specifies or imposes requirements, constraints, or circumstances that must be satisfied or hold true for another entity or situation.
-
C.
areAffectedBy
Indicates that one entity experiences an effect, influence, or impact as a result of another entity or event.
-
D.
conditionalEffect
Indicates that one event, state, or action occurs or holds only if a specified condition is met.
-
E.
canImpact
chosen
Indicates that one entity has the potential or ability to affect, influence, or cause a change in 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_69f348eb327881909b4584b925742f6e |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6b49436b0819094e21603054d05d4 |
completed | May 3, 2026, 2:36 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a7bdb481908d16a32f49e38c2c |
completed | May 3, 2026, 2:32 a.m. |
Created at: April 30, 2026, 11:50 p.m.