Triple
T3054809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aarhus University |
E60454
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
AU
Aarhus University (AU) is a major public research university in Aarhus, Denmark, known for its broad range of academic programs and strong international profile.
|
E323675
|
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: AU | Statement: [Aarhus University, abbreviation, AU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AU Context triple: [Aarhus University, abbreviation, AU]
-
A.
AU
AU is the commonly used abbreviation for the African Union, a continental organization that promotes political and economic cooperation among African states.
-
B.
AUD
AUD is the stock ticker symbol for Audacy, Inc., a major American audio and radio broadcasting company.
-
C.
Australia
Australia is a large island continent and sovereign country in the Southern Hemisphere, known for its unique wildlife, diverse landscapes, and major cities such as Sydney and Melbourne.
-
D.
Australia/Sydney
Australia/Sydney is the IANA time zone identifier representing the local civil time for Sydney, Australia, including its daylight saving transitions.
-
E.
ANZ
ANZ is the ICAO airline designator used to identify Air New Zealand in international aviation operations.
- 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: AU Triple: [Aarhus University, abbreviation, AU]
Generated description
Aarhus University (AU) is a major public research university in Aarhus, Denmark, known for its broad range of academic programs and strong international profile.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: AU Target entity description: Aarhus University (AU) is a major public research university in Aarhus, Denmark, known for its broad range of academic programs and strong international profile.
-
A.
AU
AU is the commonly used abbreviation for the African Union, a continental organization that promotes political and economic cooperation among African states.
-
B.
AUD
AUD is the stock ticker symbol for Audacy, Inc., a major American audio and radio broadcasting company.
-
C.
Australia
Australia is a large island continent and sovereign country in the Southern Hemisphere, known for its unique wildlife, diverse landscapes, and major cities such as Sydney and Melbourne.
-
D.
Australia/Sydney
Australia/Sydney is the IANA time zone identifier representing the local civil time for Sydney, Australia, including its daylight saving transitions.
-
E.
ANZ
ANZ is the ICAO airline designator used to identify Air New Zealand in international aviation operations.
- 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_69ad8578137c81908259dcb27c7d6d7c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ad9bf6b9948190bc957bfd1579c471 |
completed | March 8, 2026, 3:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1ef03425c8190a44486ab563c210f |
completed | March 11, 2026, 10:38 p.m. |
| NEDg | Description generation | batch_69b1f2d6e2008190adad44758e2d4766 |
completed | March 11, 2026, 10:55 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b1f34005c88190817c40dc30f99f14 |
completed | March 11, 2026, 10:57 p.m. |
Created at: March 8, 2026, 3:02 p.m.