Triple
T13572073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruovesi |
E324187
|
entity |
| Predicate | hasNeighboringMunicipality |
P224
|
FINISHED |
| Object | Kihniö |
E840380
|
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: Kihniö | Statement: [Ruovesi, hasNeighboringMunicipality, Kihniö]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kihniö Context triple: [Ruovesi, hasNeighboringMunicipality, Kihniö]
-
A.
Kihniö
chosen
Kihniö is a small rural municipality in western Finland known for its forests, lakes, and location within the Pirkanmaa region.
-
B.
Kihlaus
Kihlaus is a comedic play by Finnish author Aleksis Kivi, known for its humorous portrayal of rural life and courtship.
-
C.
Kuhmoinen
Kuhmoinen is a rural municipality in Finland known for its lakeside landscapes, forests, and outdoor recreation opportunities.
-
D.
Keilaniemi
Keilaniemi is a coastal district in Espoo, Finland, known as a major business hub hosting numerous corporate headquarters and high-rise office buildings.
-
E.
Kihikihi
Kihikihi is a small town in New Zealand’s Waikato region, known for its rural character and proximity to the larger center of Te Awamutu.
- 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_69d80769100c819099111274614f5ed2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb0106cb48190b20eb9bda131a68a |
completed | April 12, 2026, 2:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f76bb827d48190958e5710d554cd04 |
completed | May 3, 2026, 3:37 p.m. |
Created at: April 9, 2026, 9:48 p.m.