Triple
T847529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trollhättan |
E18308
|
entity |
| Predicate | hasAttraction |
P105
|
FINISHED |
| Object | Trollhättan locks |
E18308
|
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: Trollhättan locks | Statement: [Trollhättan, hasAttraction, Trollhättan locks]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trollhättan locks Context triple: [Trollhättan, hasAttraction, Trollhättan locks]
-
A.
Trollhättan
chosen
Trollhättan is a city in western Sweden known for its historic role in the automotive industry and as the longtime home of Saab Automobile’s main production facilities.
-
B.
Strömstad
Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
-
C.
Östersund
Östersund is a city in central Sweden known for its strong winter sports tradition and repeated bids to host the Winter Olympics.
-
D.
Linköping
Linköping is a major city in southern Sweden known for its university, high-tech industry, and historic cathedral.
-
E.
Tyresö Municipality
Tyresö Municipality is a suburban coastal municipality in eastern Sweden known for its proximity to Stockholm and its mix of residential areas, forests, and archipelago landscapes.
- 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_69a4938b04208190b82e1df6b572c548 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac0ba6b4819089c15ed7e1765502 |
completed | March 1, 2026, 9:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7b8472f188190b470893c76b20ccf |
completed | March 4, 2026, 4:42 a.m. |
Created at: March 1, 2026, 7:38 p.m.