Triple
T1669075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lolita Pulido |
E36081
|
entity |
| Predicate | loveInterestOf |
P7325
|
FINISHED |
| Object | Don Diego Vega |
E87903
|
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: Don Diego Vega | Statement: [Lolita Pulido, loveInterestOf, Don Diego Vega]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Don Diego Vega Context triple: [Lolita Pulido, loveInterestOf, Don Diego Vega]
-
A.
Don Diego Vega
chosen
Don Diego Vega is the secret identity of Zorro, a masked vigilante nobleman who defends the oppressed in early 19th-century California.
-
B.
Armando Diaz
Armando Diaz was an Italian general best known for leading Italy to victory on the Italian Front during World War I, particularly at the Battle of Vittorio Veneto.
-
C.
Joaquín Toesca
Joaquín Toesca was an 18th-century Italian-born architect who became a key figure in Chilean neoclassical architecture.
-
D.
Gabriel Valencia
Gabriel Valencia was a 19th-century Mexican general and political figure who played a significant role in Mexico’s military and governmental affairs, including during the Mexican–American War.
-
E.
Raúl
Raúl is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
- 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_69a8861286808190939afff3ce8ee31e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90adf3d3c81909233e574e79b82a2 |
completed | March 5, 2026, 4:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad683461ec8190b442054443c472b3 |
completed | March 8, 2026, 12:14 p.m. |
Created at: March 4, 2026, 7:29 p.m.