Triple
T2960150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victor Hedman |
E80026
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object |
Örnsköldsvik
Örnsköldsvik is a coastal town in northern Sweden known for its strong ice hockey tradition and as the hometown of several prominent NHL players.
|
E335730
|
NE FINISHED |
How this triple was built (4 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: Örnsköldsvik | Statement: [Victor Hedman, placeOfBirth, Örnsköldsvik]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Örnsköldsvik Context triple: [Victor Hedman, placeOfBirth, Örnsköldsvik]
-
A.
Östersund
Östersund is a city in central Sweden known for its strong winter sports tradition and repeated bids to host the Winter Olympics.
-
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.
Norrköping
Norrköping is a historic industrial city in eastern Sweden known for its preserved textile mills, waterways, and cultural institutions.
-
E.
Trollhättan
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.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Örnsköldsvik Triple: [Victor Hedman, placeOfBirth, Örnsköldsvik]
Generated description
Örnsköldsvik is a coastal town in northern Sweden known for its strong ice hockey tradition and as the hometown of several prominent NHL players.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Örnsköldsvik Target entity description: Örnsköldsvik is a coastal town in northern Sweden known for its strong ice hockey tradition and as the hometown of several prominent NHL players.
-
A.
Östersund
Östersund is a city in central Sweden known for its strong winter sports tradition and repeated bids to host the Winter Olympics.
-
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.
Norrköping
Norrköping is a historic industrial city in eastern Sweden known for its preserved textile mills, waterways, and cultural institutions.
-
E.
Trollhättan
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.
- F. None of above. chosen
Provenance (5 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_69ad8b1341848190bd19dbf46892887d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad992dd4248190b5f3d4f342593b8c |
completed | March 8, 2026, 3:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b24b079a808190adcbac948ad067e9 |
completed | March 12, 2026, 5:11 a.m. |
| NEDg | Description generation | batch_69b24c78cb408190948f715254175cff |
completed | March 12, 2026, 5:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b24d2ce888819087cc7c3f5db0e859 |
completed | March 12, 2026, 5:20 a.m. |
Created at: March 8, 2026, 2:57 p.m.