Triple
T34715723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quota 90 |
E1000766
|
entity |
| Predicate | exchangeRateTarget |
P92667
|
FINISHED |
| Object | 90 lire per 1 pound sterling |
—
|
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: 90 lire per 1 pound sterling | Statement: [Quota 90, exchangeRateTarget, 90 lire per 1 pound sterling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exchangeRateTarget Context triple: [Quota 90, exchangeRateTarget, 90 lire per 1 pound sterling]
-
A.
exchangeCurrency
Indicates a relationship where one party converts or trades an amount of one currency for an equivalent amount of another currency.
-
B.
currencyExchangeRate
chosen
Indicates the rate at which one currency can be exchanged for another.
-
C.
exchangeRateToPoundSterling
Indicates the rate at which one unit of a given currency can be converted into British pounds sterling.
-
D.
exchangeRateCharacteristic
Indicates a relationship where a specific property or feature is attributed to an exchange rate, characterizing how that rate behaves or is defined.
-
E.
referenceForExchangeRates
Indicates that something serves as the authoritative source or benchmark used to determine or look up exchange rates between currencies.
- 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_69f76dad3f108190a280fd0a2f4ee89a |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f77ffa6b68819090257fed3802c239 |
completed | May 3, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69f7795978c481909e152cd1bd02dd07 |
completed | May 3, 2026, 4:35 p.m. |
Created at: May 3, 2026, 3:59 p.m.