Triple
T13216152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UIS |
E314621
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | UIS |
E314621
|
NE 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: UIS | Statement: [UIS, abbreviation, UIS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: UIS Context triple: [UIS, abbreviation, UIS]
-
A.
UIS
chosen
UIS is a public university in Springfield, Illinois, known for its liberal arts and professional programs within the University of Illinois system.
-
B.
UI
UI is the commonly used abbreviation for the University of Indonesia, one of the country’s leading public universities.
-
C.
UI
UI is the commonly used abbreviation for the University of Iceland, the country’s leading public research university located in Reykjavík.
-
D.
UIT
UIT is the IATA airport code for the airfield serving Jaluit Atoll in the Marshall Islands.
-
E.
UIF
UIF is Mexico’s Financial Intelligence Unit responsible for analyzing and combating money laundering and terrorist financing through oversight of financial operations.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d806aee7308190b70a237ba2a6e3e1 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf28c9c819080d7b42d20f579d1 |
completed | April 10, 2026, 11:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6ff1ebf648190a27d11b3dc494446 |
completed | May 3, 2026, 7:54 a.m. |
Created at: April 9, 2026, 9:18 p.m.