Triple
T16737446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brunkebergstorg |
E406752
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Hamngatan |
E378314
|
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: Hamngatan | Statement: [Brunkebergstorg, locatedNear, Hamngatan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hamngatan Context triple: [Brunkebergstorg, locatedNear, Hamngatan]
-
A.
Hamngatan
chosen
Hamngatan is a major shopping and traffic street in central Stockholm, Sweden, known for its department stores and proximity to Sergels torg.
-
B.
Banérgatan
Banérgatan is a street in central Stockholm, Sweden, running through the Östermalm district and connecting to the major square and traffic hub Karlaplan.
-
C.
Hagestein
Hagestein is a small village in the Dutch province of Utrecht, known for its historic church and rural character along the Lek River.
-
D.
Örgrytevägen
Örgrytevägen is a major street in Gothenburg, Sweden, connecting the central area around Korsvägen with the district of Örgryte and serving as an important urban thoroughfare.
-
E.
Torggata
Torggata is a central street in Oslo, Norway, known for its mix of shops, cafés, bars, and pedestrian-friendly urban life.
- 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_69d8838ffb088190a0b11149929006bf |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e39c3b60fc81908cf331448b4b5598 |
completed | April 18, 2026, 2:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a51c5c388190a88f8bd67dbac82e |
completed | May 10, 2026, 3:32 p.m. |
Created at: April 10, 2026, 5:20 a.m.