Triple
T6978538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kalmar |
E161776
|
entity |
| Predicate | locatedSouthOf |
P9676
|
FINISHED |
| Object |
Oskarshamn
Oskarshamn is a coastal town in southeastern Sweden known for its Baltic Sea harbor and proximity to the island of Gotland.
|
E690171
|
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: Oskarshamn | Statement: [Kalmar, locatedSouthOf, Oskarshamn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oskarshamn Context triple: [Kalmar, locatedSouthOf, Oskarshamn]
-
A.
Eskilstuna
Eskilstuna is an industrial city in central Sweden known historically for its metalworking and engineering industries.
-
B.
Sundsvall
Sundsvall is a coastal city in central Sweden known as an important industrial and commercial center on the Gulf of Bothnia.
-
C.
Karlskoga
Karlskoga is an industrial town in central Sweden known for its historical association with Alfred Nobel and its role in the country’s arms and engineering industries.
-
D.
Örebro
Örebro is a historic city in central Sweden known for its medieval castle, university, and role as a regional economic and cultural hub.
-
E.
Norrköping
Norrköping is a historic industrial city in eastern Sweden known for its preserved textile mills, waterways, and cultural institutions.
- 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: Oskarshamn Triple: [Kalmar, locatedSouthOf, Oskarshamn]
Generated description
Oskarshamn is a coastal town in southeastern Sweden known for its Baltic Sea harbor and proximity to the island of Gotland.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Oskarshamn Target entity description: Oskarshamn is a coastal town in southeastern Sweden known for its Baltic Sea harbor and proximity to the island of Gotland.
-
A.
Eskilstuna
Eskilstuna is an industrial city in central Sweden known historically for its metalworking and engineering industries.
-
B.
Sundsvall
Sundsvall is a coastal city in central Sweden known as an important industrial and commercial center on the Gulf of Bothnia.
-
C.
Karlskoga
Karlskoga is an industrial town in central Sweden known for its historical association with Alfred Nobel and its role in the country’s arms and engineering industries.
-
D.
Örebro
Örebro is a historic city in central Sweden known for its medieval castle, university, and role as a regional economic and cultural hub.
-
E.
Norrköping
Norrköping is a historic industrial city in eastern Sweden known for its preserved textile mills, waterways, and cultural institutions.
- 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_69c68855dc0481909b4c7e9e9ed273db |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6db68d25c8190a1776908619ad979 |
completed | March 27, 2026, 7:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c91f3e6cec8190ad66e8f4feb6b911 |
completed | March 29, 2026, 12:46 p.m. |
| NEDg | Description generation | batch_69c9206a41388190a40a5bf39ab50e0d |
completed | March 29, 2026, 12:51 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c920bcd7a0819096bcc4cb36e6c4f3 |
completed | March 29, 2026, 12:53 p.m. |
Created at: March 27, 2026, 2:31 p.m.