Triple
T2912254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Niels Henrik Abel |
E63708
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Niels |
E63708
|
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: Niels | Statement: [Niels Henrik Abel, givenName, Niels]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Niels Context triple: [Niels Henrik Abel, givenName, Niels]
-
A.
Niels
chosen
Niels is the given name of the pioneering Norwegian mathematician Niels Henrik Abel, known for his foundational work in algebra and analysis.
-
B.
Søren
Søren is a masculine given name of Scandinavian origin, most famously borne by the Danish philosopher Søren Kierkegaard.
-
C.
Nils Norman
Nils Norman is a business figure known for co-founding the biotechnology company Biogen.
-
D.
Henrik
Henrik is the given name of the renowned Norwegian mathematician Niels Henrik Abel, known for his pioneering work in algebra and analysis.
-
E.
Jens
Jens is a masculine given name commonly used in Scandinavian and German-speaking countries, equivalent to "John" in English.
- 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_69ab4c44ab448190b9411324e8a1fc1d |
completed | March 6, 2026, 9:51 p.m. |
| NER | Named-entity recognition | batch_69abe0eb77708190b745b887f3b9a618 |
completed | March 7, 2026, 8:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b0562014fc8190b7b702fa40682382 |
completed | March 10, 2026, 5:34 p.m. |
Created at: March 6, 2026, 10:11 p.m.