Triple
T199682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zimbabwean dollar |
E4073
|
entity |
| Predicate | firstSeriesCode |
P8050
|
FINISHED |
| Object | ZWD |
—
|
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: ZWD | Statement: [Zimbabwean dollar, firstSeriesCode, ZWD]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstSeriesCode Context triple: [Zimbabwean dollar, firstSeriesCode, ZWD]
-
A.
firstOf
Indicates that one entity is the earliest or initial member in an ordered sequence or collection relative to the others.
-
B.
firstStandardized
Indicates that an entity is the earliest or primary instance to which a standard or uniform specification has been first applied among comparable entities.
-
C.
firstLetter
Indicates that one entity is the initial character or starting letter of another entity (typically a string or word).
-
D.
isSeriesOf
Indicates that one entity is a sequence or set of related items that collectively form a series associated with another entity.
-
E.
currentSeriesIntroduced
Indicates that an entity was first introduced or appeared in the currently ongoing series or installment of a work.
- 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_69a254bca59881909a15e1496f1508c7 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a25bcc6dc88190b8c24b485588dfe4 |
completed | Feb. 28, 2026, 3:06 a.m. |
| PD | Predicate disambiguation | batch_69a25b4886b48190b46fd2244648a098 |
completed | Feb. 28, 2026, 3:04 a.m. |
| PDg | Predicate description generation | batch_69a25bc6ba208190aa8bec59d32f95fd |
completed | Feb. 28, 2026, 3:06 a.m. |
Created at: Feb. 28, 2026, 2:44 a.m.