Triple
T9741493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Wedding Ringer |
E236195
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Jorge Garcia |
E389691
|
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: Jorge Garcia | Statement: [The Wedding Ringer, starring, Jorge Garcia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jorge Garcia Context triple: [The Wedding Ringer, starring, Jorge Garcia]
-
A.
Jorge Garcia
chosen
Jorge Garcia is an American actor and comedian best known for his role as Hugo "Hurley" Reyes on the television series Lost.
-
B.
Greg Garcia
Greg Garcia is an American television writer and producer best known for creating the sitcom "My Name Is Earl."
-
C.
Jaime Carbonell
Jaime Carbonell was a prominent computer scientist and pioneer in machine learning and natural language processing, best known for founding the Language Technologies Institute at Carnegie Mellon University.
-
D.
Kevin Alejandro
Kevin Alejandro is an American actor known for his roles in television series such as Southland, True Blood, and Lucifer.
-
E.
Eduardo Molina
Eduardo Molina is a Mexico City Metro station on Line 5 serving the northeastern area of the city.
- 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_69ca84d3e24481908a476e2231123cf9 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9f2af3e48190b83a442cd0e84062 |
completed | April 1, 2026, 10:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1aff2339c8190b164b13b54a40cec |
completed | April 5, 2026, 12:42 a.m. |
Created at: March 30, 2026, 8:23 p.m.