Triple
T14028366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rio Ferdinand |
E337522
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Rio
Rio is a masculine given name used in various cultures, often associated with the Spanish and Portuguese word for "river" and popularized by figures in sports and entertainment.
|
E1081075
|
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: Rio | Statement: [Rio Ferdinand, givenName, Rio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rio Context triple: [Rio Ferdinand, givenName, Rio]
-
A.
Rio
"Rio" is a song featured on Mika's album "No Place in Heaven."
-
B.
Rio
Rio is a young, talented hacker and one of the central robbers in the Spanish television series "Money Heist" (La Casa de Papel).
-
C.
Rio
Rio is a settlement located within the municipality of Elba, an island in the Tyrrhenian Sea off the coast of Italy.
-
D.
Rio
"Rio" is a 1982 new wave pop song by Duran Duran, best known for its catchy melody, vibrant production, and iconic music video set in exotic yacht-filled locations.
-
E.
Rio
Rio is a creative work, likely a film or artistic project, associated with Jenico Damasco.
- 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: Rio Triple: [Rio Ferdinand, givenName, Rio]
Generated description
Rio is a masculine given name used in various cultures, often associated with the Spanish and Portuguese word for "river" and popularized by figures in sports and entertainment.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rio Target entity description: Rio is a masculine given name used in various cultures, often associated with the Spanish and Portuguese word for "river" and popularized by figures in sports and entertainment.
-
A.
Rio
Rio is a creative work, likely a film or artistic project, associated with Jenico Damasco.
-
B.
Rio
Rio is a young, talented hacker and one of the central robbers in the Spanish television series "Money Heist" (La Casa de Papel).
-
C.
Rio
Rio is a coastal town in western Greece, near the city of Patras, known for its strategic location by the Gulf of Patras and the Rio–Antirrio Bridge connecting the Peloponnese to mainland Greece.
-
D.
Rio
"Rio" is a 1982 new wave pop song by Duran Duran, best known for its catchy melody, vibrant production, and iconic music video set in exotic yacht-filled locations.
-
E.
Rio
Rio is a 2011 animated adventure-comedy film set in Brazil that follows a domesticated macaw’s journey of self-discovery amid vibrant music and colorful Rio de Janeiro scenery.
- 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_69d81c6543a48190bd5ba93d7419e797 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2fa830ac81908cb7df7c9e81e42a |
completed | April 14, 2026, 12:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdef7a6d881909297d74ae60f7681 |
completed | May 7, 2026, 6:50 p.m. |
| NEDg | Description generation | batch_69fce0b657d48190bad13a2b47e7f7d4 |
completed | May 7, 2026, 6:57 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fce164e3d48190b35a7019deada72c |
completed | May 7, 2026, 7 p.m. |
Created at: April 9, 2026, 10:20 p.m.