Triple
T4446286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Østfold |
E96296
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Askim |
E51185
|
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: Askim | Statement: [Østfold, contains, Askim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Askim Context triple: [Østfold, contains, Askim]
-
A.
Askim
chosen
Askim is a town in southeastern Norway that serves as one of the locations for Østfold University College’s campuses.
-
B.
Asake
Asake is a Nigerian singer and songwriter known for his energetic fusion of Afrobeats, amapiano, and street-pop, and for being one of the standout artists on Olamide’s YBNL Nation label.
-
C.
Atsugi
Atsugi is a city in Kanagawa Prefecture, Japan, known as a regional commercial and industrial center with convenient access to the Tokyo metropolitan area.
-
D.
Asago
Asago is a city in northern Hyōgo Prefecture, Japan, known for its mountainous scenery, historic castle ruins, and hot spring resorts.
-
E.
Asaka
Asaka is a Japanese noble family name historically associated with a collateral branch of the Imperial Family, including Prince Asaka Yasuhiko.
- 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_69b345415ba481908df738e7174448ba |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b355d1eba08190899d0a3c1684ce4e |
completed | March 13, 2026, 12:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b613850eb88190b689a632b0e2b374 |
completed | March 15, 2026, 2:03 a.m. |
Created at: March 12, 2026, 11:32 p.m.