Triple
T964048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Usk |
E20796
|
entity |
| Predicate | hasPostTown |
P2711
|
FINISHED |
| Object | USK |
E20796
|
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: USK | Statement: [Usk, hasPostTown, USK]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: USK Context triple: [Usk, hasPostTown, USK]
-
A.
Usk
chosen
Usk is a small historic town in Monmouthshire, southeast Wales, known for its medieval castle and picturesque setting on the River Usk.
-
B.
USZ
USZ is a major public teaching hospital in Zurich, Switzerland, affiliated with the University of Zurich and known for its advanced medical care and research.
-
C.
The U
The U is the widely recognized nickname and athletic brand of the University of Miami, especially associated with its prominent Hurricanes sports programs.
-
D.
The U
The U is the popular nickname of the Philadelphia Union, a professional Major League Soccer club based in the Philadelphia metropolitan area.
-
E.
Unger
Unger is a German-origin surname borne by various notable individuals across fields such as politics, arts, and academia.
- 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_69a493b21f2881908132dcf45dcd2f36 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b4303e5881909d101d11f9732c75 |
completed | March 1, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac11a6107481909b152291a73958d3 |
completed | March 7, 2026, 11:53 a.m. |
Created at: March 1, 2026, 7:40 p.m.