Triple
T7905981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leslie Mann |
E183575
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Rio |
E62222
|
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: Rio | Statement: [Leslie Mann, notableWork, Rio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rio Context triple: [Leslie Mann, notableWork, Rio]
-
A.
Rio
chosen
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.
-
B.
Rio
Rio is a settlement located within the municipality of Elba, an island in the Tyrrhenian Sea off the coast of Italy.
-
C.
Rio
Rio is a young, talented hacker and one of the central robbers in the Spanish television series "Money Heist" (La Casa de Papel).
-
D.
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.
-
E.
Paraná River
The Paraná River is one of South America's longest and most important rivers, flowing through Brazil, Paraguay, and Argentina and serving as a key waterway for transport, hydroelectric power, and regional ecosystems.
- 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_69ca828dec0c81908b8f55a4dbbb53ff |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a56c9f0819094dc87fe55a8823e |
completed | March 31, 2026, 3:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccec781ac88190b52305beaa213415 |
completed | April 1, 2026, 9:59 a.m. |
Created at: March 30, 2026, 5:03 p.m.