Triple
T27494774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TZ |
E693993
|
entity |
| Predicate | denotesCountryWithCurrency |
P39835
|
FINISHED |
| Object | Tanzanian shilling |
—
|
NE NERFINISHED |
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: Tanzanian shilling | Statement: [TZ, denotesCountryWithCurrency, Tanzanian shilling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: denotesCountryWithCurrency Context triple: [TZ, denotesCountryWithCurrency, Tanzanian shilling]
-
A.
currencyCountry
chosen
Indicates that a given currency is officially used as legal tender in a particular country.
-
B.
currencyCodeDenoted
Indicates that a specific currency code is used to denote or represent a particular currency.
-
C.
denominationCountry
Indicates the country with which a particular denomination (such as a currency or religious denomination) is officially associated or recognized.
-
D.
currencyFamily
Indicates that two currencies belong to the same broader monetary family or classification, typically sharing a common origin, standard, or structural framework.
-
E.
currencyArea
Indicates that one entity is the geographic or economic region in which the other entity’s currency is officially used or valid.
- 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_69ef5382b9648190be0b1ef2ad5d043c |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69f64dbbaefc8190952b8320bf4397d8 |
completed | May 2, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69f64cacd2c08190aed8a1761d0da679 |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 27, 2026, 1:07 p.m.