Triple
T821740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lillehammer |
E17762
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Innlandet |
E65742
|
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: Innlandet | Statement: [Lillehammer, locatedIn, Innlandet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Innlandet Context triple: [Lillehammer, locatedIn, Innlandet]
-
A.
Innlandet
chosen
Innlandet is a county in eastern Norway known for its inland landscapes, including mountains, forests, and important winter sports venues.
-
B.
Trøndelag
Trøndelag is a central region of Norway known for its historic city of Trondheim, coastal landscapes, and strong cultural traditions.
-
C.
Ringerike
Ringerike is a historic district and municipality in southeastern Norway known for its rich Viking-age heritage and distinctive cultural traditions.
-
D.
Nordland
Nordland is a long coastal county in northern Norway known for its dramatic fjords, islands like the Lofoten archipelago, and Arctic landscapes.
-
E.
Indre
Indre is a river in central France that flows through the regions of Berry and Touraine before joining the Loire.
- 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_69a4937bcaac8190a322524ac6f45a5a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ab7aea38819092a0860ec6e2a033 |
completed | March 1, 2026, 9:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7928f8a808190aaf5f2a2f3ee676f |
completed | March 4, 2026, 2:01 a.m. |
Created at: March 1, 2026, 7:38 p.m.