Triple
T1837269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swedish Army |
E41092
|
entity |
| Predicate | garrison |
P75
|
FINISHED |
| Object | Halmstad |
E218044
|
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: Halmstad | Statement: [Swedish Army, garrison, Halmstad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Halmstad Context triple: [Swedish Army, garrison, Halmstad]
-
A.
Halmstad
chosen
Halmstad is a coastal city in southwestern Sweden known for its historic town center, harbor, and role as a strategic site in Scandinavian conflicts.
-
B.
Sundsvall
Sundsvall is a coastal city in central Sweden known as an important industrial and commercial center on the Gulf of Bothnia.
-
C.
Nyköping
Nyköping is a historic coastal town in southeastern Sweden known for its medieval castle, harbor, and role as a regional administrative and cultural center.
-
D.
Lund
Lund is a common Scandinavian surname of Swedish origin.
-
E.
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.
- 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_69a88647f9388190909bc36e795bdaec |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb0380a4c81909a2ad0bfd97c884a |
completed | March 7, 2026, 4:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af5cb503bc8190823a843bb58d85e1 |
completed | March 9, 2026, 11:50 p.m. |
Created at: March 4, 2026, 7:33 p.m.