Triple
T5697770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jordbro |
E125580
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Västerhaninge |
E125579
|
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: Västerhaninge | Statement: [Jordbro, locatedNear, Västerhaninge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Västerhaninge Context triple: [Jordbro, locatedNear, Västerhaninge]
-
A.
Västerhaninge
chosen
Västerhaninge is a suburban locality in Stockholm County, Sweden, known as a residential community within the Haninge area.
-
B.
Strängnäs
Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
-
C.
Mönsterås
Mönsterås is a small coastal town and municipality in Kalmar County, southeastern Sweden, known for its Baltic Sea shoreline and traditional Swedish countryside.
-
D.
Tärnsjö
Tärnsjö is a small locality in central Sweden known for its rural setting and traditional leather tanning industry.
-
E.
Östervåla
Östervåla is a locality in central Sweden that serves as one of the settlements within Heby Municipality in Uppsala County.
- 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_69c0082c96988190b3a6a201edce472a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0240d6c0c8190bf970c7652fd9573 |
completed | March 22, 2026, 5:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07ddd0f248190a796055212284542 |
completed | March 22, 2026, 11:40 p.m. |
Created at: March 22, 2026, 3:45 p.m.