Triple
T23997237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kannon Caviar Cross |
E594130
|
entity |
| Predicate | mayBeAvailableIn |
P154561
|
FINISHED |
| Object | licensed dispensaries (where legal) |
—
|
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: licensed dispensaries (where legal) | Statement: [Kannon Caviar Cross, mayBeAvailableIn, licensed dispensaries (where legal)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayBeAvailableIn Context triple: [Kannon Caviar Cross, mayBeAvailableIn, licensed dispensaries (where legal)]
-
A.
availableInCountry
Indicates that something can be legally or practically obtained, accessed, or used within a specified country.
-
B.
availableAs
Indicates that one entity can be used, accessed, or offered in the form, role, or capacity of another entity.
-
C.
availableWith
Indicates that one entity can be obtained, accessed, or used in conjunction with another entity.
-
D.
availableFor
Indicates that one entity can be used, accessed, or allocated for the benefit, purpose, or use of another entity.
-
E.
availableInMode
Indicates that something can be used, accessed, or functions within a specified mode or operational setting.
- 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_69e288b9ecf08190b8c94a278f5674fe |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d39066f8819096d13bfdd0a047fc |
completed | April 29, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69f1615994c48190a5de95d3f7e5cd0a |
completed | April 29, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f16e35944c8190b57cfa31f1e9da1b |
completed | April 29, 2026, 2:34 a.m. |
Created at: April 17, 2026, 9:38 p.m.