Triple
T21032593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hisingen |
E518099
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Eriksberg
Eriksberg is a waterfront district and former shipyard area in Gothenburg, Sweden, known for its redeveloped residential and commercial spaces along the Göta älv river.
|
E1464072
|
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: Eriksberg | Statement: [Hisingen, contains, Eriksberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eriksberg Context triple: [Hisingen, contains, Eriksberg]
-
A.
Rosersberg
Rosersberg is a locality in Stockholm County, Sweden, known for its historic Rosersberg Palace and its location near Stockholm Arlanda Airport.
-
B.
Blackeberg
Blackeberg is a suburban district in western Stockholm, Sweden, best known internationally as the bleak, wintry backdrop of the Swedish vampire novel and film "Let the Right One In."
-
C.
Hallsberg
Hallsberg is a Swedish railway town in Örebro County known as a major junction in the national rail network.
-
D.
Enebyberg
Enebyberg is a residential suburban area in the northern part of the Stockholm urban region in Sweden.
-
E.
Ulriksdal
Ulriksdal is a district in Solna, Sweden, known for the historic Ulriksdal Palace and its surrounding parklands along the Edsviken inlet.
- 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: Eriksberg Triple: [Hisingen, contains, Eriksberg]
Generated description
Eriksberg is a waterfront district and former shipyard area in Gothenburg, Sweden, known for its redeveloped residential and commercial spaces along the Göta älv river.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Eriksberg Target entity description: Eriksberg is a waterfront district and former shipyard area in Gothenburg, Sweden, known for its redeveloped residential and commercial spaces along the Göta älv river.
-
A.
Rosersberg
Rosersberg is a locality in Stockholm County, Sweden, known for its historic Rosersberg Palace and its location near Stockholm Arlanda Airport.
-
B.
Blackeberg
Blackeberg is a suburban district in western Stockholm, Sweden, best known internationally as the bleak, wintry backdrop of the Swedish vampire novel and film "Let the Right One In."
-
C.
Hallsberg
Hallsberg is a Swedish railway town in Örebro County known as a major junction in the national rail network.
-
D.
Enebyberg
Enebyberg is a residential suburban area in the northern part of the Stockholm urban region in Sweden.
-
E.
Ulriksdal
Ulriksdal is a district in Solna, Sweden, known for the historic Ulriksdal Palace and its surrounding parklands along the Edsviken inlet.
- 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_69e0b503275c8190afd9a163f997c709 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc83828c81909c1ec745c0313c9f |
completed | April 21, 2026, 4:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a094747bcec8190beadedbe6dde96d0 |
completed | May 17, 2026, 4:42 a.m. |
| NEDg | Description generation | batch_6a094a3eaef881908083e8f7e03f4f07 |
completed | May 17, 2026, 4:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a094aa6baf8819088ccc84f41640bf6 |
completed | May 17, 2026, 4:57 a.m. |
Created at: April 16, 2026, 1:56 p.m.