Triple
T11920133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cheddar cheese |
E283630
|
entity |
| Predicate | agingEffect |
P99952
|
FINISHED |
| Object | flavor becomes sharper 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: flavor becomes sharper with age | Statement: [Cheddar cheese, agingEffect, flavor becomes sharper with age]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: agingEffect Context triple: [Cheddar cheese, agingEffect, flavor becomes sharper with age]
-
A.
visualEffect
Indicates that one entity produces, modifies, or is associated with a particular visual effect on another entity or within a scene.
-
B.
eventEffect
Indicates the resulting change, outcome, or consequence that one event has on another state, entity, or event.
-
C.
effectOnUser
Indicates how an action, event, or condition influences or impacts a user.
-
D.
emotionEffect
Indicates that one entity’s emotional state causes or influences a change in another entity’s feelings, behavior, or condition.
-
E.
ultimateEffect
chosen
Indicates the final or overall outcome that results from a preceding action, condition, or sequence of events.
- 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_69d6ab2c07e88190ba13b0d21fd6cf33 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8e8dff77481908cacf6ad03df34ac |
completed | April 10, 2026, 12:11 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3632ac8190b13e53c2b5db7125 |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:45 p.m.