Triple
T8714443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oktoberfestbier |
E206859
|
entity |
| Predicate | typicalHopCharacter |
P84039
|
FINISHED |
| Object | low to moderate bitterness |
—
|
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: low to moderate bitterness | Statement: [Oktoberfestbier, typicalHopCharacter, low to moderate bitterness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalHopCharacter Context triple: [Oktoberfestbier, typicalHopCharacter, low to moderate bitterness]
-
A.
typicalFigure
Indicates that one entity serves as a standard or representative example (a typical instance) of the other entity.
-
B.
franchiseCharacter
Indicates a relationship where a character belongs to, appears in, or is part of a particular media franchise.
-
C.
musicalCharacter
Indicates that one entity is a character or role that appears within the other entity, which is a musical work or production.
-
D.
touristCharacter
Indicates that an entity has the role, behavior, or qualities characteristic of a tourist in relation to another entity or context.
-
E.
typicalBlendPartner
Indicates that two entities are commonly or characteristically combined or mixed together as standard or usual partners.
- 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_69ca83572d4881909bef3be2b578d539 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5cd6707c819092c9fca34f273d5e |
completed | March 31, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69cc456e806c819087e7d66ee737f242 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc46c40c54819093d174a4203f9515 |
completed | March 31, 2026, 10:12 p.m. |
Created at: March 30, 2026, 6:35 p.m.