Triple
T1052696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Öland |
E22734
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Färjestaden
Färjestaden is a coastal town on the Swedish island of Öland, known as a key gateway via the Öland Bridge to the mainland city of Kalmar.
|
E138814
|
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: Färjestaden | Statement: [Öland, hasTown, Färjestaden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Färjestaden Context triple: [Öland, hasTown, Färjestaden]
-
A.
Strömstad
Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
-
B.
Port of Gothenburg
The Port of Gothenburg is Scandinavia’s largest seaport and a major logistics hub for Swedish international trade.
-
C.
Faro
Faro is a historic coastal city in southern Portugal that serves as the capital of the Algarve region and a major gateway for tourism.
-
D.
Old Town, Stockholm
Old Town, Stockholm is the historic medieval center of Sweden’s capital, known for its cobblestone streets, colorful buildings, and major institutions like the Swedish Academy and the Royal Palace.
-
E.
Arendal
Arendal is a coastal town and municipality in southern Norway known historically as a regional political and trading center.
- 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: Färjestaden Triple: [Öland, hasTown, Färjestaden]
Generated description
Färjestaden is a coastal town on the Swedish island of Öland, known as a key gateway via the Öland Bridge to the mainland city of Kalmar.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Färjestaden Target entity description: Färjestaden is a coastal town on the Swedish island of Öland, known as a key gateway via the Öland Bridge to the mainland city of Kalmar.
-
A.
Strömstad
Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
-
B.
Port of Gothenburg
The Port of Gothenburg is Scandinavia’s largest seaport and a major logistics hub for Swedish international trade.
-
C.
Faro
Faro is a historic coastal city in southern Portugal that serves as the capital of the Algarve region and a major gateway for tourism.
-
D.
Old Town, Stockholm
Old Town, Stockholm is the historic medieval center of Sweden’s capital, known for its cobblestone streets, colorful buildings, and major institutions like the Swedish Academy and the Royal Palace.
-
E.
Arendal
Arendal is a coastal town and municipality in southern Norway known historically as a regional political and trading center.
- 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_69a493da02e081908c13ff5e02a0fe7a |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8b644088190a1f0f00f97941298 |
completed | March 1, 2026, 10:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac8303cbec8190a3b8a9bad2434ee7 |
completed | March 7, 2026, 7:56 p.m. |
| NEDg | Description generation | batch_69ac83a2d15c8190abd20fa3a98b89cf |
completed | March 7, 2026, 7:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac84131858819097330fb693b3f0bd |
completed | March 7, 2026, 8:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.