Triple
T282970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | G77 |
E5828
|
entity |
| Predicate | foundedInCity |
P263
|
FINISHED |
| Object | Geneva |
E414
|
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: Geneva | Statement: [G77, foundedInCity, Geneva]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Geneva Context triple: [G77, foundedInCity, Geneva]
-
A.
Geneva
chosen
Geneva is a major Swiss city on Lake Geneva known for hosting numerous international organizations, including United Nations agencies and the Red Cross.
-
B.
Zurich
Zurich is the largest city in Switzerland, known as a global financial hub and cultural center situated on the shores of Lake Zurich.
-
C.
Geneva metropolitan area
The Geneva metropolitan area is the cross-border urban region centered on the city of Geneva, spanning parts of Switzerland and France and functioning as a major international, financial, and diplomatic hub.
-
D.
Neuchâtel
Neuchâtel is a French-speaking canton in western Switzerland known for its lakeside capital, watchmaking industry, and historic architecture.
-
E.
Lausanne, Switzerland
Lausanne, Switzerland is a picturesque city on the shores of Lake Geneva known for its role as an Olympic capital and its vibrant cultural and academic 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_69a25946a7ac8190a78871c210213272 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NER | Named-entity recognition | batch_69a25e0c14b48190a5c936bab36180b3 |
completed | Feb. 28, 2026, 3:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4b5ce2ff88190ac180c4df9604028 |
completed | March 1, 2026, 9:55 p.m. |
Created at: Feb. 28, 2026, 3:02 a.m.