Triple
T400804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Halden |
E9275
|
entity |
| Predicate | administrativeCenter |
P1474
|
FINISHED |
| Object | Halden (town) |
E9275
|
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: Halden (town) | Statement: [Halden, administrativeCenter, Halden (town)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Halden (town) Context triple: [Halden, administrativeCenter, Halden (town)]
-
A.
Halden
chosen
Halden is a historic border town and municipality in southeastern Norway, known for the Fredriksten fortress and its location near the Swedish border.
-
B.
Gaustad
Gaustad is a district in Oslo, Norway, known for hosting major academic and research institutions, including parts of the University of Oslo campus.
-
C.
Tøyen
Tøyen is a neighborhood in Oslo, Norway, known for its cultural institutions, parks, and educational facilities.
-
D.
Sokndal municipality
Sokndal municipality is a coastal municipality in Rogaland county, southwestern Norway, known for its rugged fjord landscape, including the historic Jøssingfjord.
-
E.
Helleren
Helleren is a small historic settlement in Norway known for its traditional houses built under a large rock overhang near the Jøssingfjord.
- 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_69a2e8004cb88190b92ed1add6abf41a |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ec8e655c819081eff85c0ef55fa5 |
completed | Feb. 28, 2026, 1:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a410410c108190990d4d5ef2e7ff61 |
completed | March 1, 2026, 10:09 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.