Triple
T1501320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minnesota |
E33799
|
entity |
| Predicate | hasStateMuffin |
P29383
|
FINISHED |
| Object | Blueberry muffin |
—
|
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: Blueberry muffin | Statement: [Minnesota, hasStateMuffin, Blueberry muffin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStateMuffin Context triple: [Minnesota, hasStateMuffin, Blueberry muffin]
-
A.
hasStatePie
Indicates that an entity possesses or is associated with a specific state-related pie (e.g., a pie representing or originating from a particular state).
-
B.
hasMemberState
Indicates that an entity includes or comprises another entity as one of its constituent member states within a larger organizational or political structure.
-
C.
hasMP
Indicates that an entity is represented by, or associated with, a specific Member of Parliament (MP).
-
D.
hasStand
Indicates that an entity possesses, is equipped with, or is supported by a stand or base structure.
-
E.
hasMood
Indicates that an entity is experiencing or characterized by a particular emotional or affective state.
- 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_69a885f352a4819099b24ff15489dede |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90584b8b881908e112c7e59163812 |
completed | March 5, 2026, 4:24 a.m. |
| PD | Predicate disambiguation | batch_69a88727ce48819089b482cdc25453d1 |
completed | March 4, 2026, 7:25 p.m. |
| PDg | Predicate description generation | batch_69a90582f2548190bc0a6bdcd6d9d015 |
completed | March 5, 2026, 4:24 a.m. |
Created at: March 4, 2026, 7:24 p.m.