Triple
T19645550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great White |
E471661
|
entity |
| Predicate | member |
P10
|
FINISHED |
| Object | Tony Montana |
—
|
NE NERFINISHED |
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: Tony Montana | Statement: [Great White, member, Tony Montana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tony Montana Context triple: [Great White, member, Tony Montana]
-
A.
Tony Montana
chosen
Tony Montana is the ruthless Cuban immigrant-turned-drug-lord protagonist of the 1983 crime film "Scarface."
-
B.
El Che
El Che is a hip-hop album by American rapper Che "Rhymefest" Smith, showcasing his socially conscious lyrics and Chicago-rooted sound.
-
C.
Emilio Largo
Emilio Largo is a fictional high-ranking SPECTRE operative and primary antagonist in the James Bond novel and film "Thunderball," known for orchestrating a nuclear extortion plot.
-
D.
Carlito
Carlito is a diminutive form of the Spanish given name Carlos, often used as an affectionate nickname.
-
E.
Cesar Odio
Cesar Odio was a longtime college basketball coach best known for leading the University of Miami men’s basketball program in the late 1980s and early 1990s.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e51395348190ac1416d46dfc6db0 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e641250e108190a707452fefc87041 |
completed | April 20, 2026, 3:07 p.m. |
Created at: April 10, 2026, 1:44 p.m.