Triple
T4830340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | "M’m! M’m! Good!" |
E107928
|
entity |
| Predicate | conveysAttribute |
P59910
|
FINISHED |
| Object | tasty |
—
|
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: tasty | Statement: ["M’m! M’m! Good!", conveysAttribute, tasty]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conveysAttribute Context triple: ["M’m! M’m! Good!", conveysAttribute, tasty]
-
A.
usesAttribute
Indicates that one entity employs, relies on, or makes use of a specific attribute of another entity in performing an action or defining a relationship.
-
B.
depictsAttribute
Indicates that one entity visually represents or illustrates a specific attribute or characteristic of another entity.
-
C.
brandAttribute
Indicates that a specific attribute or characteristic is associated with, or describes, a particular brand.
-
D.
attributeType
Indicates that one entity specifies the kind or category of attribute that characterizes another entity.
-
E.
commonAttribute
Indicates that two or more entities share the same specified attribute or property.
- 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_69bd43fac8188190803f0327190621e4 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1fe130819087ae01309f96a0c8 |
completed | March 20, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69bd6dda5e808190a26ec85e4499d8e4 |
completed | March 20, 2026, 3:55 p.m. |
Created at: March 20, 2026, 1:24 p.m.