Triple
T11735949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raahe |
E279025
|
entity |
| Predicate | oldTownKnownFor |
P67817
|
FINISHED |
| Object | wooden town architecture |
—
|
LITERAL 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: wooden town architecture | Statement: [Raahe, oldTownKnownFor, wooden town architecture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oldTownKnownFor Context triple: [Raahe, oldTownKnownFor, wooden town architecture]
-
A.
oldTownStatus
Indicates that a place holds the designation or characteristics of being an old or historic town.
-
B.
traditionallyKnownFor
chosen
Indicates that something is widely and historically recognized or reputed for a particular characteristic, activity, product, or role.
-
C.
oldestTownIn
Indicates that a town is the most ancient or earliest established town within a specified larger area or region.
-
D.
historicalTownName
Indicates that the object is a former or historical name by which the town (subject) was previously known.
-
E.
primaryCityLandmarkOf
Indicates that a landmark is a principal or defining landmark associated with a specific city.
- F. None of above.
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_69d6aaffec6881908bead509e8621742 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4edced48190b7a59dd45921828e |
completed | April 10, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69d88a7f51248190bf492bd7509b5413 |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:41 p.m.