Triple
T13857159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | France Médias Monde |
E333095
|
entity |
| Predicate | subsidiary |
P258
|
FINISHED |
| Object |
RFI
RFI (Radio France Internationale) is a French public radio station that broadcasts news and cultural programming worldwide in multiple languages.
|
E1066935
|
NE FINISHED |
How this triple was built (4 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: RFI | Statement: [France Médias Monde, subsidiary, RFI]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RFI Context triple: [France Médias Monde, subsidiary, RFI]
-
A.
RFI
RFI is the Italian state-owned company responsible for managing and maintaining Italy’s national railway infrastructure.
-
B.
RF
RF was the squadron code used to identify No. 303 Polish Fighter Squadron, a renowned Polish unit that fought alongside the Royal Air Force during World War II.
-
C.
RF
RF is the stock ticker symbol for Regions Financial Corporation, a major U.S. regional bank headquartered in Birmingham, Alabama.
-
D.
.rf
.rf is the Cyrillic country-code top-level domain representing the Russian Federation on the internet.
-
E.
RFA
RFA is the ship prefix used by vessels of the Royal Fleet Auxiliary, the civilian-manned fleet that supports the United Kingdom’s Royal Navy with logistical and operational services.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: RFI Triple: [France Médias Monde, subsidiary, RFI]
Generated description
RFI (Radio France Internationale) is a French public radio station that broadcasts news and cultural programming worldwide in multiple languages.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: RFI Target entity description: RFI (Radio France Internationale) is a French public radio station that broadcasts news and cultural programming worldwide in multiple languages.
-
A.
RFI
RFI is the Italian state-owned company responsible for managing and maintaining Italy’s national railway infrastructure.
-
B.
RF
RF was the squadron code used to identify No. 303 Polish Fighter Squadron, a renowned Polish unit that fought alongside the Royal Air Force during World War II.
-
C.
RF
RF is the stock ticker symbol for Regions Financial Corporation, a major U.S. regional bank headquartered in Birmingham, Alabama.
-
D.
.rf
.rf is the Cyrillic country-code top-level domain representing the Russian Federation on the internet.
-
E.
RFA
RFA is the ship prefix used by vessels of the Royal Fleet Auxiliary, the civilian-manned fleet that supports the United Kingdom’s Royal Navy with logistical and operational services.
- F. None of above. chosen
Provenance (5 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_69d81c5ba13c8190839315f54768acfd |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02dc9f488190b7181dcb7e304632 |
completed | April 14, 2026, 9:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c0fb7c3c819081fc6f89aa17d6af |
completed | May 3, 2026, 9:41 p.m. |
| NEDg | Description generation | batch_69f7c2c711948190ac614291592a7e03 |
completed | May 3, 2026, 9:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7c36f28b48190b734a9e5e7ae39b9 |
completed | May 3, 2026, 9:51 p.m. |
Created at: April 9, 2026, 10:14 p.m.