Triple
T16312982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marc Rich |
E396102
|
entity |
| Predicate | residence |
P75
|
FINISHED |
| Object | Zug |
E187177
|
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: Zug | Statement: [Marc Rich, residence, Zug]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zug Context triple: [Marc Rich, residence, Zug]
-
A.
Zug
chosen
Zug is a small, affluent Swiss city and canton known for its low taxes, picturesque lakeside setting, and role as a hub for international businesses and cryptocurrency companies.
-
B.
Türnich
Türnich is a district of the town of Kerpen in North Rhine-Westphalia, Germany, known as a residential area within the Cologne metropolitan region.
-
C.
Olten
Olten is a town in the canton of Solothurn in northwestern Switzerland, known as an important railway junction and regional economic center.
-
D.
Kloten
Kloten is a town in the canton of Zurich in northern Switzerland, best known as the home of Zurich Airport.
-
E.
Bülach
Bülach is a town in northern Switzerland that serves as a regional center near Zurich, known for its residential character and proximity to Zurich Airport.
- 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_69d87f23bb088190a16fbb91a1957ea5 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e288dc30f48190b508220429b66e92 |
completed | April 17, 2026, 7:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a001fa6ceb48190b937a15b94fd3cfa |
completed | May 10, 2026, 6:03 a.m. |
Created at: April 10, 2026, 5:06 a.m.