Triple
T6941395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexander Semin |
E160680
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Semin |
E160680
|
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: Semin | Statement: [Alexander Semin, familyName, Semin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Semin Context triple: [Alexander Semin, familyName, Semin]
-
A.
Semin
chosen
Semin is a Russian surname most notably borne by former NHL winger Alexander Semin.
-
B.
Seminara
Seminara is a historic town in the Calabria region of southern Italy, known for its medieval heritage and religious significance.
-
C.
SEMAL
SEMAL is the UN/LOCODE designation for the port and transport location associated with Lake Mälaren in Sweden.
-
D.
SEJ
SEJ is the ICAO airline designator assigned to SpiceJet, a major low-cost carrier based in India.
-
E.
Semnoz
Semnoz is a mountain in the French Alps known for its panoramic views over Lake Annecy and its popular hiking, skiing, and cycling routes.
- 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_69c6884f3db4819080ad65da69386206 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6da65d4788190a83625f96c867ffe |
completed | March 27, 2026, 7:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7515bb4688190a81bef732676eb4e |
completed | March 28, 2026, 3:56 a.m. |
Created at: March 27, 2026, 2:28 p.m.