Triple
T5538593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Slovenian tolar |
E145230
|
entity |
| Predicate | ISO4217Code |
P189
|
FINISHED |
| Object |
SIT
SIT was the ISO 4217 currency code for the Slovenian tolar, the former national currency of Slovenia before adoption of the euro.
|
E528123
|
NE FINISHED |
How this triple was built (4 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: SIT | Statement: [Slovenian tolar, ISO4217Code, SIT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SIT Context triple: [Slovenian tolar, ISO4217Code, SIT]
-
A.
SITELLE
SITELLE is an advanced imaging Fourier transform spectrometer used on the Canada–France–Hawaii Telescope to obtain detailed spectral and spatial information across extended astronomical objects.
-
B.
SAIT
SAIT is a Canadian polytechnic institute in Calgary, Alberta, offering career-focused technical, trades, and applied degree programs.
-
C.
SUT
SUT is the commonly used abbreviation for Sharif University of Technology, a leading science and engineering university in Iran.
-
D.
SIF
SIF is the governing body for ice hockey in Sweden, overseeing the national teams and domestic competitions.
-
E.
Siatista
Siatista is a historic town in Western Macedonia, Greece, known for its traditional mansions, fur trade, and cultural heritage.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: SIT Triple: [Slovenian tolar, ISO4217Code, SIT]
Generated description
SIT was the ISO 4217 currency code for the Slovenian tolar, the former national currency of Slovenia before adoption of the euro.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SIT Target entity description: SIT was the ISO 4217 currency code for the Slovenian tolar, the former national currency of Slovenia before adoption of the euro.
-
A.
SITELLE
SITELLE is an advanced imaging Fourier transform spectrometer used on the Canada–France–Hawaii Telescope to obtain detailed spectral and spatial information across extended astronomical objects.
-
B.
SAIT
SAIT is a Canadian polytechnic institute in Calgary, Alberta, offering career-focused technical, trades, and applied degree programs.
-
C.
SUT
SUT is the commonly used abbreviation for Sharif University of Technology, a leading science and engineering university in Iran.
-
D.
SIF
SIF is the governing body for ice hockey in Sweden, overseeing the national teams and domestic competitions.
-
E.
Siatista
Siatista is a historic town in Western Macedonia, Greece, known for its traditional mansions, fur trade, and cultural heritage.
- F. None of above. chosen
Provenance (5 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_69c008fa64888190adae56c8f9ea4031 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01fb2fe488190808e02ce5aabb2ad |
completed | March 22, 2026, 4:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c02817cb04819088df72950c791144 |
completed | March 22, 2026, 5:34 p.m. |
| NEDg | Description generation | batch_69c033df2c7881909660eb931908318c |
completed | March 22, 2026, 6:24 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c034640cd081909b44ff23e9005e57 |
completed | March 22, 2026, 6:26 p.m. |
Created at: March 22, 2026, 3:35 p.m.