Triple
T18500228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SSR |
E452046
|
entity |
| Predicate | hasSubsidiary |
P254
|
FINISHED |
| Object | RTS |
—
|
NE NERFINISHED |
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: RTS | Statement: [SSR, hasSubsidiary, RTS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RTS Context triple: [SSR, hasSubsidiary, RTS]
-
A.
RTS
chosen
RTS is a major Russian securities exchange that facilitates trading in stocks, bonds, and other financial instruments.
-
B.
RTS
RTS is the Swiss public broadcasting organization that provides French-language radio, television, and digital media services.
-
C.
RTS
RTS is the commonly used abbreviation for Widzew Łódź, a historic Polish football club based in Łódź.
-
D.
RTSI
RTSI is the commonly used abbreviation for the RTS Index, a benchmark stock market index tracking major companies listed on the Moscow Exchange.
-
E.
RTM
RTM is the commonly used abbreviation for Rosetta Terminology Mapping, a system for standardizing and aligning terminology across different datasets or domains.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d3855d50819097fc8561b0299dd9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e532c3810c81908fa329c177c6d96c |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 11:36 a.m.