Triple
T12877541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ugly Betty |
E308006
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Tony Plana |
E307631
|
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: Tony Plana | Statement: [Ugly Betty, starring, Tony Plana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tony Plana Context triple: [Ugly Betty, starring, Tony Plana]
-
A.
Tony Plana
chosen
Tony Plana is a Cuban-American actor and director best known for his role as Ignacio Suarez on the television series "Ugly Betty."
-
B.
Tony Almeida
Tony Almeida is a key fictional Counter Terrorist Unit agent in the television series "24," known for his complex loyalties and evolving role across multiple seasons.
-
C.
Mark Palermo
Mark Palermo is a Canadian film critic and screenwriter best known for co-writing the cult horror-comedy film "Detention."
-
D.
Danny Tamberelli
Danny Tamberelli is an American actor, comedian, and musician best known for his childhood roles on Nickelodeon shows like The Adventures of Pete & Pete and All That.
-
E.
Danny Tenaglia
Danny Tenaglia is an American DJ and producer renowned for his influential role in house music and the New York club scene.
- 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_69d7bdf69bc48190af6c2621f28ca351 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d970fa8474819086a8af3c90f3ca84 |
completed | April 10, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6a55393a88190a88c9357a6db5aec |
completed | May 3, 2026, 1:30 a.m. |
Created at: April 9, 2026, 5:38 p.m.