Triple
T5431026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Segeltorp |
E121488
|
entity |
| Predicate | hasNeighbouringArea |
P17964
|
FINISHED |
| Object |
Sätra
Sätra is a suburban district in southwestern Stockholm, Sweden, known for its residential areas and proximity to Lake Mälaren.
|
E519643
|
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: Sätra | Statement: [Segeltorp, hasNeighbouringArea, Sätra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sätra Context triple: [Segeltorp, hasNeighbouringArea, Sätra]
-
A.
Motala
Motala is a town in southern Sweden known for its location on Lake Vättern and its historic role as an industrial and canal hub.
-
B.
Sieda
Sieda is the surname of Abdulbaset Sieda, a Syrian-Kurdish academic and opposition political figure.
-
C.
Sulak
Sulak is a Thai social activist and Buddhist scholar known for his advocacy of human rights, democracy, and engaged Buddhism.
-
D.
Haga Södra
Haga Södra is a southern district of the Haga area in Stockholm, Sweden, known for its proximity to central city streets and parklands.
-
E.
Setra
Setra is a German brand of premium coaches and buses known for its high-quality engineering and comfort, produced by Daimler AG.
- 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: Sätra Triple: [Segeltorp, hasNeighbouringArea, Sätra]
Generated description
Sätra is a suburban district in southwestern Stockholm, Sweden, known for its residential areas and proximity to Lake Mälaren.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sätra Target entity description: Sätra is a suburban district in southwestern Stockholm, Sweden, known for its residential areas and proximity to Lake Mälaren.
-
A.
Motala
Motala is a town in southern Sweden known for its location on Lake Vättern and its historic role as an industrial and canal hub.
-
B.
Sieda
Sieda is the surname of Abdulbaset Sieda, a Syrian-Kurdish academic and opposition political figure.
-
C.
Sulak
Sulak is a Thai social activist and Buddhist scholar known for his advocacy of human rights, democracy, and engaged Buddhism.
-
D.
Haga Södra
Haga Södra is a southern district of the Haga area in Stockholm, Sweden, known for its proximity to central city streets and parklands.
-
E.
Setra
Setra is a German brand of premium coaches and buses known for its high-quality engineering and comfort, produced by Daimler AG.
- 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_69bd463c65f0819082ee6483ab4b466a |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd883e5e10819091e159dfd245e94d |
completed | March 20, 2026, 5:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf3ac6285081909afa6e91a023f6d5 |
completed | March 22, 2026, 12:41 a.m. |
| NEDg | Description generation | batch_69bf3c43ffe88190b8d2a10ea8a9a455 |
completed | March 22, 2026, 12:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf3ce7d6388190a9cd22f76f4420e0 |
completed | March 22, 2026, 12:50 a.m. |
Created at: March 20, 2026, 2:06 p.m.