Triple
T9634394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Definition of Standard ML |
E232891
|
entity |
| Predicate | influenced |
P9
|
FINISHED |
| Object | Moscow ML |
E807597
|
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: Moscow ML | Statement: [The Definition of Standard ML, influenced, Moscow ML]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moscow ML Context triple: [The Definition of Standard ML, influenced, Moscow ML]
-
A.
Moscow ML
chosen
Moscow ML is a lightweight, educationally oriented implementation of the Standard ML programming language, known for its simplicity and support for formal methods and teaching.
-
B.
Moscufo
Moscufo is a small Italian town and comune in the Abruzzo region, noted for its historic architecture and rural setting.
-
C.
Moskovici
Moskovici is a variant spelling of the surname Moskovitz, which is of Eastern European Jewish origin.
-
D.
Khimki
Khimki is a city in Moscow Oblast, Russia, forming part of the Moscow metropolitan area and known for its proximity to major transport hubs and industrial facilities.
-
E.
BC Dynamo Moscow
BC Dynamo Moscow is a professional basketball club from Moscow, Russia, historically associated with the Dynamo sports society and known for competing in national and European competitions.
- 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_69ca848940cc8190b97cec654cb3bb4a |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9b2a0e2c8190ab5aaa223b1e1cde |
completed | April 1, 2026, 10:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d18237e2608190a3e7d45231a35efd |
completed | April 4, 2026, 9:27 p.m. |
Created at: March 30, 2026, 8:11 p.m.