Triple
T2925129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martin Ødegaard |
E78824
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Drammen, Norway |
E105261
|
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: Drammen, Norway | Statement: [Martin Ødegaard, placeOfBirth, Drammen, Norway]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Drammen, Norway Context triple: [Martin Ødegaard, placeOfBirth, Drammen, Norway]
-
A.
Lysaker, Norway
Lysaker, Norway is a suburban area in Bærum just west of Oslo, known as a residential and commercial hub and historically associated with notable figures such as explorer Fridtjof Nansen.
-
B.
Ballangen, Norway
Ballangen, Norway is a small former mining municipality in Nordland county known for its scenic fjord landscape in Northern Norway.
-
C.
Drammen
chosen
Drammen is a city and municipality in southeastern Norway known for its riverside setting along the Drammenselva and its role as a regional commercial and transport hub.
-
D.
Porsgrunn
Porsgrunn is an industrial and port city in Telemark county in southeastern Norway, known for its porcelain production and location along the Telemark Canal.
-
E.
Kongsberg
Kongsberg is a Norwegian town known for its historic silver mines and its modern high-tech and defense industries.
- 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_69ad8b0d40b481908bc2a5fa2e73c3fb |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad97c086888190ba51ce659a6c4f50 |
completed | March 8, 2026, 3:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b0563a81788190b94fab34e41a76e7 |
completed | March 10, 2026, 5:34 p.m. |
Created at: March 8, 2026, 2:55 p.m.