Triple
T13471683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | mainland Norway |
E311642
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Hamar |
E68670
|
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: Hamar | Statement: [mainland Norway, contains, Hamar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hamar Context triple: [mainland Norway, contains, Hamar]
-
A.
Hamar
chosen
Hamar is a town and municipality in Innlandet county, Norway, known for its rich Viking history and as a regional cultural and administrative center.
-
B.
Hemsila
Hemsila is a river in the Norwegian municipality of Hemsedal, known for its scenic valley course and popular trout fishing.
-
C.
Garmsar
Garmsar is a city in Semnan Province of north-central Iran, known as a regional transport hub and gateway between Tehran and eastern parts of the country.
-
D.
Ahlat
Ahlat is a historic town in eastern Turkey renowned for its medieval Seljuk-era cemeteries and monuments on the northwestern shore of Lake Van.
-
E.
Harahan
Harahan is a small suburban city in the Greater New Orleans area of Louisiana, known for its residential character and proximity to the Mississippi River.
- 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_69d806a938b8819097ec43a2229fc7f9 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf22e5f88190b1078f006c8ef7c0 |
completed | April 12, 2026, 2:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7462d97688190b5b817fff5973ceb |
completed | May 3, 2026, 12:57 p.m. |
Created at: April 9, 2026, 9:42 p.m.