Triple
T2659663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portrait Series banknotes |
E54695
|
entity |
| Predicate | reverseTheme |
P13703
|
FINISHED |
| Object | education (on some denominations) |
—
|
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: education (on some denominations) | Statement: [Portrait Series banknotes, reverseTheme, education (on some denominations)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reverseTheme Context triple: [Portrait Series banknotes, reverseTheme, education (on some denominations)]
-
A.
themeContrast
Indicates a relationship where two themes are compared or opposed to highlight their differences or tension.
-
B.
reverseFeature
chosen
Indicates that one feature is the inverse or opposite counterpart of another feature in a given context.
-
C.
themeFor
Indicates that something serves as the central subject, topic, or focus for another thing (such as an event, work, or activity).
-
D.
reversed
Indicates that the direction or order of a previously defined relationship or sequence between entities is inverted.
-
E.
theme
Indicates the entity that is the primary participant or content affected or characterized by an action, event, or state.
- 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_69ab49e028948190b97e01d73548b1d9 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd94f3b1881909bd36cfe61c254a5 |
completed | March 7, 2026, 7:52 a.m. |
| PD | Predicate disambiguation | batch_69abd81768748190bd965f367cf6ef37 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:53 p.m.