Triple
T8096126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valbo Church |
E188990
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Valbo |
E35825
|
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: Valbo | Statement: [Valbo Church, locatedIn, Valbo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Valbo Context triple: [Valbo Church, locatedIn, Valbo]
-
A.
Valbo
chosen
Valbo is a locality in Gävleborg County, Sweden, known as the hometown of NHL ice hockey star Nicklas Bäckström.
-
B.
Vanylven
Vanylven is a coastal municipality in western Norway known for its fjords, mountains, and rural communities.
-
C.
Vallentuna
Vallentuna is a locality in Stockholm County, Sweden, known as a suburban community within the Stockholm metropolitan area.
-
D.
Velda
Velda is the loyal and resourceful secretary and love interest of private investigator Mike Hammer in the hardboiled crime novel and film "Kiss Me Deadly."
-
E.
Tyvholm
Tyvholm is one of the small Danish islands that form part of the Hirsholmene archipelago in the Kattegat.
- 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_69ca82b886d88190a9cba0d5a4a27521 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4291f1d4819098985ac2b20b6c75 |
completed | March 31, 2026, 3:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc9407df3481908353e8468b49e6bc |
completed | April 1, 2026, 3:42 a.m. |
Created at: March 30, 2026, 5:30 p.m.