Triple
T200220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ForMemRS |
E4087
|
entity |
| Predicate | relatedTitle |
P914
|
FINISHED |
| Object | FRS |
E6383
|
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: FRS | Statement: [ForMemRS, relatedTitle, FRS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FRS Context triple: [ForMemRS, relatedTitle, FRS]
-
A.
FRS
chosen
FRS is the post-nominal title used by Fellows of the Royal Society, denoting distinguished scientists elected to the United Kingdom’s national academy of sciences.
-
B.
FRB
FRB is the commonly used abbreviation for the Federal Reserve Board of Governors, the central governing body of the U.S. Federal Reserve System that oversees national monetary policy and banking regulation.
-
C.
FRA
FRA is the three-letter ISO 3166-1 alpha-3 country code that uniquely identifies France in international standards and data systems.
-
D.
FRA
FRA is the United States government agency responsible for regulating and overseeing the nation’s railroad safety, infrastructure, and operations.
-
E.
FÜ
FÜ is the vehicle registration code used on license plates for the city of Fürth in Bavaria, Germany.
- 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_69a254bca59881909a15e1496f1508c7 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a25be47ea881909c296b30a0d47a65 |
completed | Feb. 28, 2026, 3:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a31c9530a88190b04a08b521fcd207 |
completed | Feb. 28, 2026, 4:49 p.m. |
Created at: Feb. 28, 2026, 2:44 a.m.