Triple
T20250114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Porsgrunds Porselænsfabrik |
E498528
|
entity |
| Predicate | hasBrand |
P1500
|
FINISHED |
| Object |
Porsgrund
Porsgrund is a Norwegian porcelain brand renowned for its high-quality tableware and long-standing design tradition.
|
E1421218
|
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: Porsgrund | Statement: [Porsgrunds Porselænsfabrik, hasBrand, Porsgrund]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Porsgrund Context triple: [Porsgrunds Porselænsfabrik, hasBrand, Porsgrund]
-
A.
Bogesund
Bogesund is a locality in Sweden known for its surrounding archipelago landscape, forests, and recreational natural areas.
-
B.
Bordesholm
Bordesholm is a small town in Schleswig-Holstein, northern Germany, historically notable as a religious and cultural center and as the burial site of regional nobility.
-
C.
Vargsundet
Vargsundet is a strait in northern Norway that connects the Altafjorden to surrounding coastal waters and separates parts of the Finnmark coastline.
-
D.
Hasselvika
Hasselvika is a small coastal village in the former Agdenes municipality in Trøndelag county, central Norway.
-
E.
Esrum Sø
Esrum Sø is one of Denmark’s largest lakes, situated in North Zealand and known for its scenic natural surroundings and recreational opportunities.
- 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: Porsgrund Triple: [Porsgrunds Porselænsfabrik, hasBrand, Porsgrund]
Generated description
Porsgrund is a Norwegian porcelain brand renowned for its high-quality tableware and long-standing design tradition.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Porsgrund Target entity description: Porsgrund is a Norwegian porcelain brand renowned for its high-quality tableware and long-standing design tradition.
-
A.
Bogesund
Bogesund is a locality in Sweden known for its surrounding archipelago landscape, forests, and recreational natural areas.
-
B.
Bordesholm
Bordesholm is a small town in Schleswig-Holstein, northern Germany, historically notable as a religious and cultural center and as the burial site of regional nobility.
-
C.
Vargsundet
Vargsundet is a strait in northern Norway that connects the Altafjorden to surrounding coastal waters and separates parts of the Finnmark coastline.
-
D.
Hasselvika
Hasselvika is a small coastal village in the former Agdenes municipality in Trøndelag county, central Norway.
-
E.
Esrum Sø
Esrum Sø is one of Denmark’s largest lakes, situated in North Zealand and known for its scenic natural surroundings and recreational opportunities.
- 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_69da6274c58c81909c646eabed6f4f30 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e673a79a208190a5a7c0f6515bc393 |
completed | April 20, 2026, 6:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0855262c548190b5f6102b4e6e01a6 |
completed | May 16, 2026, 11:29 a.m. |
| NEDg | Description generation | batch_6a0856ac50e081909c8bc737e4fe6e56 |
completed | May 16, 2026, 11:36 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a085746f2f08190a703a832f5867c7b |
completed | May 16, 2026, 11:38 a.m. |
Created at: April 11, 2026, 11:41 p.m.