Triple
T17173241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Worldwide Universities Network |
E416789
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | WUN |
E416789
|
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: WUN | Statement: [Worldwide Universities Network, abbreviation, WUN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WUN Context triple: [Worldwide Universities Network, abbreviation, WUN]
-
A.
WUN
WUN is the vehicle registration code for the district of Wunsiedel im Fichtelgebirge in Upper Franconia, Germany.
-
B.
WUN
chosen
WUN is a global consortium of research-intensive universities that collaborate on international education and research initiatives.
-
C.
WUN
WUN is the commonly used abbreviation for Western United FC, a professional soccer club based in Victoria, Australia that competes in the A-League Men.
-
D.
WU
WU is the stock ticker symbol for Western Union, a global financial services company best known for its money transfer and payment services.
-
E.
WU
WU is a leading European university in Vienna specializing in economics, business, and social sciences.
- 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_69d886d5f34c8190b24564dfaa63f3fb |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3fc0b7c9c819082e503cb493d7e7b |
completed | April 18, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0148415c788190a4248b097f323d03 |
completed | May 11, 2026, 3:08 a.m. |
Created at: April 10, 2026, 5:37 a.m.