Triple
T6305816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grimsby |
E141371
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Tromsø |
E56624
|
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: Tromsø | Statement: [Grimsby, hasTwinTown, Tromsø]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tromsø Context triple: [Grimsby, hasTwinTown, Tromsø]
-
A.
Tromsø
chosen
Tromsø is a city in northern Norway known for its Arctic location, vibrant cultural scene, and prominence as a viewing spot for the Northern Lights.
-
B.
Bodø
Bodø is a coastal city in northern Norway known as a regional hub for culture, transport, and access to Arctic nature.
-
C.
Trondheim
Trondheim is a historic Norwegian city in Trøndelag county, known for its medieval Nidaros Cathedral and role as a former capital of Norway.
-
D.
Ålesund
Ålesund is a coastal Norwegian city renowned for its distinctive Art Nouveau architecture and location across several islands in Western Norway.
-
E.
Kristiansund
Kristiansund is a coastal city in western Norway known for its historic clipfish industry, distinctive layout across several islands, and picturesque harbor.
- 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_69c008cf0ad4819095def81e2bd42f9f |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06479acec819090306a155a03b774 |
completed | March 22, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7b89caf148190a2959698e5849e12 |
completed | March 28, 2026, 11:16 a.m. |
Created at: March 22, 2026, 4:28 p.m.