Triple
T2183990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rector of Uppsala University |
E49108
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Uppsala |
E36359
|
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: Uppsala | Statement: [Rector of Uppsala University, locatedIn, Uppsala]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Uppsala Context triple: [Rector of Uppsala University, locatedIn, Uppsala]
-
A.
Uppsala
chosen
Uppsala is a historic Swedish city north of Stockholm, known for its prestigious university, medieval cathedral, and role as a cultural and ecclesiastical center.
-
B.
Sundsvall
Sundsvall is a coastal city in central Sweden known as an important industrial and commercial center on the Gulf of Bothnia.
-
C.
Lund
Lund is a historic city in southern Sweden known for its medieval cathedral, prestigious university, and role as a significant cultural and academic center in Scandinavia.
-
D.
Lund
Lund is a common Scandinavian surname of Swedish origin.
-
E.
Umeå
Umeå is a university city in northern Sweden known for its cultural scene, research institutions, and role as a regional economic hub.
- 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_69a88aa72d348190a9544bb5b8a4e71d |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbf0e92248190a9449fce4044438a |
completed | March 7, 2026, 6 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae654016a88190a242d43491f0726c |
completed | March 9, 2026, 6:14 a.m. |
Created at: March 4, 2026, 7:45 p.m.