Triple
T9866340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barbour Silver Company |
E239840
|
entity |
| Predicate | markingPractice |
P74486
|
FINISHED |
| Object | used maker’s marks on bases of items |
—
|
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: used maker’s marks on bases of items | Statement: [Barbour Silver Company, markingPractice, used maker’s marks on bases of items]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: markingPractice Context triple: [Barbour Silver Company, markingPractice, used maker’s marks on bases of items]
-
A.
marksOn
Indicates that one entity bears visible signs, traces, or imprints that have been made or left by another entity.
-
B.
marks
Indicates that one entity makes a visible or symbolic sign on, or designates, another entity for identification, emphasis, or distinction.
-
C.
coversPractice
chosen
Indicates that one entity includes, addresses, or provides instruction on a particular practice or set of practices.
-
D.
distinctiveMarking
Indicates that one entity bears a unique or distinguishing visual feature or pattern that sets it apart from others.
-
E.
mentionsPractice
Indicates that one entity refers to, discusses, or brings up a particular practice in some form of communication.
- 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_69ca84e7506c819095cbde4ff16512bb |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3d091e48190b10463562d0dc461 |
completed | April 2, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69cd1d7621d48190aa6a6f34399514b0 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:36 p.m.