Triple
T4566466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hven |
E121920
|
entity |
| Predicate | DanishName |
P5200
|
FINISHED |
| Object | Hven |
E121920
|
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: Hven | Statement: [Hven, DanishName, Hven]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hven Context triple: [Hven, DanishName, Hven]
-
A.
Hven
chosen
Hven is a small Danish island in the Øresund Strait, historically renowned as the site of astronomer Tycho Brahe’s pioneering observatories and research center.
-
B.
Hein
Hein is a Dutch surname most notably borne by Piet Hein, a renowned 17th-century naval officer and folk hero of the Dutch Republic.
-
C.
Helleren
Helleren is a small historic settlement in Norway known for its traditional houses built under a large rock overhang near the Jøssingfjord.
-
D.
Kven
Kven is a Finnic minority language closely related to Finnish, traditionally spoken by the Kven people in northern Norway.
-
E.
Hanno
Hanno is a city in Saitama Prefecture, Japan, known for its natural scenery, hiking spots, and proximity to the Tokyo metropolitan area.
- 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_69bd463f156881908a99aca69c5721ac |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd589e35808190aa609bb04b128dbe |
completed | March 20, 2026, 2:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdd3b560a08190a485e9ec45e0f0f8 |
completed | March 20, 2026, 11:09 p.m. |
Created at: March 20, 2026, 1:09 p.m.