Triple
T35900529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Right Bank Bordeaux wines |
E1038339
|
entity |
| Predicate | agingCharacteristics |
P184223
|
FINISHED |
| Object | develop truffle notes with age |
—
|
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: develop truffle notes with age | Statement: [Right Bank Bordeaux wines, agingCharacteristics, develop truffle notes with age]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: agingCharacteristics Context triple: [Right Bank Bordeaux wines, agingCharacteristics, develop truffle notes with age]
-
A.
AICharacteristics
Indicates the defining traits, behaviors, or properties that characterize an artificial intelligence system.
-
B.
agingCharacter
Indicates that a character is undergoing the process of growing older or experiencing age-related change over time.
-
C.
ownerCharacterization
Indicates how an owner is characterized or described in relation to the entity they own.
-
D.
APACharacteristics
Indicates that one entity specifies or describes the attributes, features, or properties of another entity.
-
E.
trackCharacteristics
Indicates the association between a track and its defining properties or attributes, such as its features, qualities, or descriptive parameters.
- 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_69f76e2190f88190beb2eed798a4ef01 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7acaec1508190a38f2ac9cc5383e7 |
completed | May 3, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f7ab734d848190a84f9b8c3a952b75 |
completed | May 3, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69f7ac2210e481909279dade5328825c |
completed | May 3, 2026, 8:12 p.m. |
Created at: May 3, 2026, 4:07 p.m.