Triple
T1261238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eagle (10-dollar gold coin) |
E12504
|
entity |
| Predicate | faceValueRelation |
P23870
|
FINISHED |
| Object | 1 eagle = 10 dollars |
—
|
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: 1 eagle = 10 dollars | Statement: [Eagle (10-dollar gold coin), faceValueRelation, 1 eagle = 10 dollars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: faceValueRelation Context triple: [Eagle (10-dollar gold coin), faceValueRelation, 1 eagle = 10 dollars]
-
A.
faceValueUnit
chosen
Indicates the unit of measurement in which the face value of something (such as a financial instrument or item) is expressed.
-
B.
semanticRelation
Indicates a general meaning-based connection between two entities, such as similarity, implication, or conceptual association.
-
C.
faceValueType
Indicates the type or category of a financial instrument’s face (nominal) value, such as how that value is defined or represented.
-
D.
value
Indicates that one entity possesses, represents, or corresponds to a particular quantity, quality, or assigned worth.
-
E.
valuedBy
Indicates that one entity is regarded as important, useful, or held in high esteem by another entity.
- 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_69a4933352e08190ac617291985e76c0 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bfc64e648190b9c4f980eb8168aa |
completed | March 1, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69a4bb6eefbc81908dddd7d2ef368186 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:50 p.m.