Triple
T20727072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sicklaön |
E509463
|
entity |
| Predicate | hasNeighborhood |
P40
|
FINISHED |
| Object |
Henriksdal
Henriksdal is a residential and waterfront district in the Sicklaön area of Nacka Municipality, just east of central Stockholm, Sweden.
|
E1512448
|
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: Henriksdal | Statement: [Sicklaön, hasNeighborhood, Henriksdal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Henriksdal Context triple: [Sicklaön, hasNeighborhood, Henriksdal]
-
A.
Hjartdal
Hjartdal is a rural municipality in Vestfold og Telemark county, Norway, known for its mountainous landscape, traditional farming communities, and historic stave church.
-
B.
Ulriksdal
Ulriksdal is a district in Solna, Sweden, known for the historic Ulriksdal Palace and its surrounding parklands along the Edsviken inlet.
-
C.
Ottosdal
Ottosdal is a small agricultural town in South Africa’s North West province, known for its grain farming and rural character.
-
D.
Ingdal
Ingdal is a small rural settlement in the municipality of Agdenes in Trøndelag county, central Norway.
-
E.
Tyssedal
Tyssedal is a small industrial village in Vestland county, Norway, known for its historic hydropower facilities and scenic location by the Sørfjorden.
- 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: Henriksdal Triple: [Sicklaön, hasNeighborhood, Henriksdal]
Generated description
Henriksdal is a residential and waterfront district in the Sicklaön area of Nacka Municipality, just east of central Stockholm, Sweden.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Henriksdal Target entity description: Henriksdal is a residential and waterfront district in the Sicklaön area of Nacka Municipality, just east of central Stockholm, Sweden.
-
A.
Hjartdal
Hjartdal is a rural municipality in Vestfold og Telemark county, Norway, known for its mountainous landscape, traditional farming communities, and historic stave church.
-
B.
Ulriksdal
Ulriksdal is a district in Solna, Sweden, known for the historic Ulriksdal Palace and its surrounding parklands along the Edsviken inlet.
-
C.
Ottosdal
Ottosdal is a small agricultural town in South Africa’s North West province, known for its grain farming and rural character.
-
D.
Ingdal
Ingdal is a small rural settlement in the municipality of Agdenes in Trøndelag county, central Norway.
-
E.
Tyssedal
Tyssedal is a small industrial village in Vestland county, Norway, known for its historic hydropower facilities and scenic location by the Sørfjorden.
- 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_69e0b4c4cc648190b45fda6e2b20af56 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c1e8b020819091d5788b90215ead |
completed | April 21, 2026, 12:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a6d6015e081909fea513c07e31ac4 |
completed | May 18, 2026, 1:37 a.m. |
| NEDg | Description generation | batch_6a0a6ebd63888190a21c3d4907b5c38a |
completed | May 18, 2026, 1:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a6f3de2e88190824c9cc266c7ee8c |
completed | May 18, 2026, 1:45 a.m. |
Created at: April 16, 2026, 12:29 p.m.