Triple
T7839983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Truls Gerhardsen |
E181780
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Gerhardsen |
E671543
|
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: Gerhardsen | Statement: [Truls Gerhardsen, familyName, Gerhardsen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gerhardsen Context triple: [Truls Gerhardsen, familyName, Gerhardsen]
-
A.
Gerhardsen
chosen
Gerhardsen is a notable Norwegian surname most prominently associated with influential 20th-century politicians and public figures in Norway.
-
B.
Gangstad
Gangstad is a small settlement located within the municipality of Inderøy in Trøndelag county, Norway.
-
C.
Hamren
Hamren is a town in the Indian state of Assam that serves as the main administrative and service center for the surrounding West Karbi Anglong region.
-
D.
Badeloch
Badeloch is a central female character in Joost van den Vondel’s Dutch play "Gijsbrecht van Aemstel," known as the loyal and tragic wife of the title hero.
-
E.
Haslum
Haslum is a suburban area in Bærum, Norway, known for its residential neighborhoods and proximity to Oslo.
- 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_69ca8285d6488190a95d4c02d7354b53 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb14c4680481908628d22bbe4842f4 |
completed | March 31, 2026, 12:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5abff2a88190a2f988b8b041ebb0 |
completed | March 31, 2026, 5:25 a.m. |
Created at: March 30, 2026, 4:47 p.m.