Triple
T5858635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lidingöbron |
E130218
|
entity |
| Predicate | crosses |
P416
|
FINISHED |
| Object | Lilla Värtan |
E110372
|
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: Lilla Värtan | Statement: [Lidingöbron, crosses, Lilla Värtan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lilla Värtan Context triple: [Lidingöbron, crosses, Lilla Värtan]
-
A.
Lilla Värtan
chosen
Lilla Värtan is a narrow strait in the inner Stockholm archipelago that separates the island of Lidingö from mainland Stockholm.
-
B.
Stora Värtan
Stora Värtan is a bay of the Baltic Sea in the Stockholm archipelago, known for its coastal residential areas, marinas, and recreational boating.
-
C.
Siljan
Siljan is a lake in Telemark, Norway, known for its scenic surroundings and proximity to the town of Skien.
-
D.
Trollbäcken
Trollbäcken is a residential suburban district in the Stockholm County area of Sweden, known for its proximity to lakes and green spaces.
-
E.
Korsnäs
Korsnäs is a small coastal municipality in western Finland known for its Swedish-speaking majority and traditional Ostrobothnian rural culture.
- 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_69c0084f3bb08190a7720f55f7aa4252 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0358654e48190908e7390a0164726 |
completed | March 22, 2026, 6:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0a1c3a69881908ffeee1ddbeb8618 |
completed | March 23, 2026, 2:13 a.m. |
Created at: March 22, 2026, 3:56 p.m.