Triple
T11773379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tony Montana |
E279955
|
entity |
| Predicate | enemy |
P4567
|
FINISHED |
| Object | Frank Lopez |
E876938
|
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: Frank Lopez | Statement: [Tony Montana, enemy, Frank Lopez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frank Lopez Context triple: [Tony Montana, enemy, Frank Lopez]
-
A.
Frank Lopez
chosen
Frank Lopez is a fictional Miami drug lord and early mentor-turned-rival to Tony Montana in the 1983 crime film "Scarface."
-
B.
Al Lopez
Al Lopez was a Hall of Fame Major League Baseball manager and former catcher best known for leading the Cleveland Indians and Chicago White Sox to American League pennants in the 1950s and early 1960s.
-
C.
David Mendoza
David Mendoza was a composer and conductor active in early 20th-century cinema, known for his work on silent film scores.
-
D.
Luis Lopez-Fitzgerald
Luis Lopez-Fitzgerald is a central romantic lead and heroic police officer in the American soap opera "Passions," known for his tumultuous relationships and family drama.
-
E.
Frank Dominguez
Frank Dominguez is an entrepreneur best known as a founder of the cloud-based software company Salesforce.
- 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_69d6ab01d2688190ad8ed6bda487eaa5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a55dfa088190a59b35d0247225e3 |
completed | April 10, 2026, 7:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f43f8a57ec8190aded70ae89aa8cf7 |
completed | May 1, 2026, 5:52 a.m. |
Created at: April 8, 2026, 9:41 p.m.