Triple
T2795697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fredrikstad |
E53030
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Borge
Borge is a district and former municipality that is now part of the city of Fredrikstad in southeastern Norway.
|
E298658
|
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: Borge | Statement: [Fredrikstad, hasSubdivision, Borge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Borge Context triple: [Fredrikstad, hasSubdivision, Borge]
-
A.
Blomstedt
Blomstedt is a surname most prominently associated with Herbert Blomstedt, a renowned Swedish conductor known for his interpretations of the classical and romantic repertoire.
-
B.
Arne
Arne is a Scandinavian masculine given name commonly used in Norway, Sweden, and Denmark.
-
C.
Svaneke
Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
-
D.
Helleren
Helleren is a small historic settlement in Norway known for its traditional houses built under a large rock overhang near the Jøssingfjord.
-
E.
Hafslund
Hafslund is a major Norwegian energy and utility company known for its role in electricity production, distribution, and related services.
- 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: Borge Triple: [Fredrikstad, hasSubdivision, Borge]
Generated description
Borge is a district and former municipality that is now part of the city of Fredrikstad in southeastern Norway.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Borge Target entity description: Borge is a district and former municipality that is now part of the city of Fredrikstad in southeastern Norway.
-
A.
Blomstedt
Blomstedt is a surname most prominently associated with Herbert Blomstedt, a renowned Swedish conductor known for his interpretations of the classical and romantic repertoire.
-
B.
Arne
Arne is a Scandinavian masculine given name commonly used in Norway, Sweden, and Denmark.
-
C.
Svaneke
Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
-
D.
Helleren
Helleren is a small historic settlement in Norway known for its traditional houses built under a large rock overhang near the Jøssingfjord.
-
E.
Hafslund
Hafslund is a major Norwegian energy and utility company known for its role in electricity production, distribution, and related services.
- 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_69ab495a90788190941b6917e1eca3a6 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abddef754081908e6218dc2208e0fd |
completed | March 7, 2026, 8:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc6646c2c81908157d8f03cb8376d |
completed | March 10, 2026, 7:21 a.m. |
| NEDg | Description generation | batch_69afc70a4e008190a846d23e1aa73bb1 |
completed | March 10, 2026, 7:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afc7907be88190b70458ed735261e8 |
completed | March 10, 2026, 7:26 a.m. |
Created at: March 6, 2026, 9:58 p.m.