Triple
T20646223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mun |
E507361
|
entity |
| Predicate | unitRelation |
P140897
|
FINISHED |
| Object | multiple coins often strung together |
—
|
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: multiple coins often strung together | Statement: [Mun, unitRelation, multiple coins often strung together]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: unitRelation Context triple: [Mun, unitRelation, multiple coins often strung together]
-
A.
valueRelation
Indicates a comparative or associative relationship between the values or magnitudes of two or more entities.
-
B.
subjectRelation
Indicates that one entity stands in a specified relational role or connection to another entity.
-
C.
termRelationTo
Indicates a general relational association between one term and another, without specifying the exact nature of that relationship.
-
D.
semanticRelation
Indicates a general meaning-based connection between two entities, such as similarity, implication, or conceptual association.
-
E.
titleRelation
Indicates a relationship where one entity serves as the title, designation, or formal name associated with another entity.
- 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_69e0b4be702c8190a3d2410a881d310a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6af1eee9c81908fd3b4fe8c4529c8 |
completed | April 20, 2026, 10:56 p.m. |
| PD | Predicate disambiguation | batch_69e5c0315f5081908098707c6455e56e |
completed | April 20, 2026, 5:57 a.m. |
| PDg | Predicate description generation | batch_69e5c3caef50819093c8159fe8d6435b |
completed | April 20, 2026, 6:12 a.m. |
Created at: April 16, 2026, 11:43 a.m.