Triple
T5645111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fisksätra |
E124365
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Saltsjöbaden |
E117385
|
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: Saltsjöbaden | Statement: [Fisksätra, locatedNear, Saltsjöbaden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saltsjöbaden Context triple: [Fisksätra, locatedNear, Saltsjöbaden]
-
A.
Saltsjöbaden
chosen
Saltsjöbaden is a coastal resort and residential area near Stockholm, Sweden, known for its historic seaside hotels, villas, and yacht harbor.
-
B.
Bollstanäs
Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
-
C.
Korsnäs
Korsnäs is a small coastal municipality in western Finland known for its Swedish-speaking majority and traditional Ostrobothnian rural culture.
-
D.
Bollnäs
Bollnäs is a small Swedish town known for its scenic lakeside setting, traditional wooden architecture, and strong bandy sports culture.
-
E.
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."
- 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_69c00824643c81909ffdb888a2d35189 |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c022a8eccc8190837d4705670dc25e |
completed | March 22, 2026, 5:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04d84e14c8190b913486cb516eee1 |
completed | March 22, 2026, 8:13 p.m. |
Created at: March 22, 2026, 3:41 p.m.