Triple
T19524979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dun Hallin broch |
E488495
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Stein |
—
|
NE NERFINISHED |
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: Stein | Statement: [Dun Hallin broch, near, Stein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stein Context triple: [Dun Hallin broch, near, Stein]
-
A.
Stein
Stein is a German-origin surname borne by numerous notable individuals across fields such as exploration, philosophy, literature, and politics.
-
B.
Stein
Stein is a municipality in the Dutch province of Limburg, known for its industrial heritage and location along the Meuse River near the Belgian border.
-
C.
Stein (SG)
chosen
Stein (SG) is a municipality in the canton of St. Gallen in northeastern Switzerland, known for its rural Alpine setting and proximity to the Toggenburg region.
-
D.
Steinman
Steinman is a surname most notably associated with David B. Steinman, an influential American civil engineer and bridge designer.
-
E.
Stange
Stange is a rural municipality in Innlandet county, Norway, known for its agricultural landscape and proximity to the town of Hamar.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8da8bec819081f400199491ccc3 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63639cfc08190894ac67f7d861a25 |
completed | April 20, 2026, 2:20 p.m. |
Created at: April 10, 2026, 1:41 p.m.