Triple
T18193425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Älvsborg Bridge |
E435599
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Älvsborg |
—
|
NE NERFINISHED |
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: Älvsborg | Statement: [Älvsborg Bridge, namedAfter, Älvsborg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Älvsborg Context triple: [Älvsborg Bridge, namedAfter, Älvsborg]
-
A.
Älvsborg
chosen
Älvsborg is a historical region in western Sweden, centered around the strategic Älvsborg Fortress that once guarded the approaches to Gothenburg and the Göta älv river.
-
B.
Södertälje Harbour
Södertälje Harbour is a key port and industrial waterfront area in Södertälje, Sweden, serving as an important hub for maritime transport and logistics.
-
C.
Skeppsbron
Skeppsbron is a historic waterfront quay and street along the eastern edge of Stockholm’s Old Town, known for its harborside views and preserved architecture.
-
D.
Lindholmen
Lindholmen is a small locality in Vallentuna Municipality in Stockholm County, Sweden, known for its residential character and proximity to natural and historical sites.
-
E.
Lindholmen
Lindholmen is a waterfront district in Gothenburg, Sweden, known as a major hub for education, research, and technology companies.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b90c7ec081909b4694ccecb449c6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e0d12b688190842375dcc5d5537c |
completed | April 19, 2026, 2:04 p.m. |
Created at: April 10, 2026, 10:31 a.m.