Triple
T6565489
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hassel |
E153893
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | Odd Hassel |
E28910
|
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: Odd Hassel | Statement: [Hassel, hasNotableBearer, Odd Hassel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Odd Hassel Context triple: [Hassel, hasNotableBearer, Odd Hassel]
-
A.
Odd Hassel
chosen
Odd Hassel was a Norwegian physical chemist and Nobel laureate renowned for his pioneering work on the structure of cyclohexane and conformational analysis in organic chemistry.
-
B.
George Hansen
George Hansen is a fictional character from the 1958 Western film "Terror in a Texas Town."
-
C.
Ole Henriksen
Ole Henriksen is a Danish skincare expert and entrepreneur best known for founding his eponymous skincare brand and popularizing spa-inspired, glow-focused beauty products.
-
D.
Erik Selvig
Erik Selvig is a fictional astrophysicist in the Marvel Cinematic Universe who becomes a close ally of Thor and plays a key role in studying and understanding cosmic phenomena.
-
E.
Ron Jensen
Ron Jensen is an American politician who has served as the mayor of Grand Prairie, Texas.
- 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_69c6880cb35881909b763eb0125236b9 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ae3cc05881908e943d3f7f8a2b1d |
completed | March 27, 2026, 4:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6e42523848190b02682e6a640ac05 |
completed | March 27, 2026, 8:10 p.m. |
Created at: March 27, 2026, 1:52 p.m.