Triple
T18441287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgy Natanson |
E450532
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Natanson |
E1002451
|
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: Natanson | Statement: [Georgy Natanson, familyName, Natanson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Natanson Context triple: [Georgy Natanson, familyName, Natanson]
-
A.
Natanson
chosen
Natanson is a surname most notably associated with Mark Natanson, a prominent Russian revolutionary and political activist of the late 19th and early 20th centuries.
-
B.
Vasishka
Vasishka was a Kushan emperor who ruled parts of northern India and Central Asia in the early 3rd century CE, known primarily from his inscriptions and coinage.
-
C.
Tatischeff
Tatischeff is the original family surname of French filmmaker and actor Jacques Tati, known for his influential comedic films and the character Monsieur Hulot.
-
D.
Eliassen
Eliassen is a Norwegian surname borne by various notable figures, including scientists, athletes, and public personalities.
-
E.
Lautenthal
Lautenthal is a small historic mining town in Germany’s Harz Mountains, known for its picturesque valley setting and former silver mining industry.
- 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_69d8d381d6388190a9e94e9c658174e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e51c10a86c819091196968b648fc92 |
completed | April 19, 2026, 6:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a040fdb4c648190aa56212c3c1e15ce |
completed | May 13, 2026, 5:44 a.m. |
Created at: April 10, 2026, 11:30 a.m.