Triple
T511400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Niels Henrik Abel |
E10615
|
entity |
| Predicate | workLocation |
P7
|
FINISHED |
| Object | Christiania |
E26400
|
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: Christiania | Statement: [Niels Henrik Abel, workLocation, Christiania]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christiania Context triple: [Niels Henrik Abel, workLocation, Christiania]
-
A.
Chocolate City
Chocolate City is a popular nickname for Washington, D.C., highlighting its historically large and influential African American population and culture.
-
B.
Sentrum
chosen
Sentrum is the central district of Oslo, Norway, which hosts some of the University of Oslo’s urban campus facilities.
-
C.
The City
The City is a common nickname for Manhattan, the densely populated and iconic borough of New York City known for its skyscrapers, cultural landmarks, and role as a global financial and media hub.
-
D.
Copenhagen
Copenhagen is the capital and largest city of Denmark, known for its historic architecture, vibrant cultural scene, and high quality of life.
-
E.
Maximum City
Maximum City is a popular nickname for Mumbai that reflects its vast scale, intense energy, and extreme contrasts in wealth, culture, and daily life.
- 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_69a2e84a0d08819087e01863fcd9abf1 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f165b91c81908c2d2ba15c64b956 |
completed | Feb. 28, 2026, 1:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4a14e37208190b4df8e75b6fe03fb |
completed | March 1, 2026, 8:27 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.