Triple
T3701831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Troms |
E80793
|
entity |
| Predicate | traditionalDistrict |
P49478
|
FINISHED |
| Object | part of Hålogaland |
—
|
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: part of Hålogaland | Statement: [Troms, traditionalDistrict, part of Hålogaland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalDistrict Context triple: [Troms, traditionalDistrict, part of Hålogaland]
-
A.
traditionalSettlement
Indicates that an entity is a settlement characterized by long-established, customary, or historically rooted patterns of habitation and land use.
-
B.
traditionalHousingRegion
Indicates the region where a group’s customary or historically established housing patterns are typically found.
-
C.
traditionalCountry
Indicates that a country is characterized by long-established customs, cultural practices, and social norms that have been preserved over time.
-
D.
urbanDistrictType
Indicates the classification of an urban district according to its specific type or category within an administrative or planning system.
-
E.
traditionalHomeVenueCity
Indicates the city that has historically served as the primary home venue location for an entity, such as a team or performer.
- F. None of above. chosen
Provenance (4 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_69ad8b1793888190a5f70e4b21dc05a1 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adc547c1848190a1ece46c59b7c43d |
completed | March 8, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69adb84eeca48190bb4de637e9f0e27a |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adb903be308190a8f1925f99e67c68 |
completed | March 8, 2026, 5:59 p.m. |
Created at: March 8, 2026, 3:33 p.m.