Triple
T2338130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue Mountains coffee |
E44358
|
entity |
| Predicate | isSubjectToCounterfeiting |
P38316
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Blue Mountains coffee, isSubjectToCounterfeiting, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isSubjectToCounterfeiting Context triple: [Blue Mountains coffee, isSubjectToCounterfeiting, true]
-
A.
isAuthentic
Indicates that something is genuine, real, or true to its claimed origin, nature, or standard.
-
B.
notLegalTenderIn
Indicates that a form of money is not officially recognized as acceptable payment within a specified jurisdiction or region.
-
C.
isLegalTenderFor
Indicates that a particular currency or form of money is officially recognized by a governing authority as valid payment for debts and financial transactions within a specified jurisdiction.
-
D.
wasLegalTender
Indicates that something was officially recognized as valid money for settling debts or transactions within a particular jurisdiction and time period.
-
E.
isLegalTenderSince
Indicates that something has held the status of legal tender starting from a specified point in time.
- 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_69a889132b488190bbb43ad4780ddd92 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abc6f75d888190a2e41edaa532e83f |
completed | March 7, 2026, 6:34 a.m. |
| PD | Predicate disambiguation | batch_69abc594087c819098100a10c5478a4b |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abc6f4245881909282b3184a288e2a |
completed | March 7, 2026, 6:34 a.m. |
Created at: March 4, 2026, 7:51 p.m.