Triple
T6412432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anthony Perkins |
E127737
|
entity |
| Predicate | performedIn |
P795
|
FINISHED |
| Object | Friendly Persuasion |
E82507
|
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: Friendly Persuasion | Statement: [Anthony Perkins, performedIn, Friendly Persuasion]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Friendly Persuasion Context triple: [Anthony Perkins, performedIn, Friendly Persuasion]
-
A.
Friendly Persuasion
chosen
Friendly Persuasion is a 1956 American drama film about a pacifist Quaker family during the American Civil War, based on Jessamyn West’s novel of the same name.
-
B.
Friendly
Friendly is the surname of Henry J. Friendly, a highly influential American judge and legal scholar known for his service on the U.S. Court of Appeals for the Second Circuit.
-
C.
FRIENDLY
FRIENDLY is the airline callsign used by Southern Airways Express, a U.S.-based commuter and regional airline.
-
D.
Please
"Please" is the 1986 synth-pop debut album by English duo Pet Shop Boys, featuring hits like "West End Girls" and "Opportunities (Let's Make Lots of Money)."
-
E.
Nice Agreement
The Nice Agreement is an international treaty that establishes a standardized classification system of goods and services used for the registration of trademarks.
- 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_69c0083723d88190b1e37b19df162c08 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c068d228208190ba05eeb7707482fe |
completed | March 22, 2026, 10:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c640c48e688190981a19ce5eb2af44 |
completed | March 27, 2026, 8:33 a.m. |
Created at: March 22, 2026, 4:42 p.m.