Triple
T8723213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jorge Carvajal (YouTube personality) |
E207063
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Carvajal |
E35546
|
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: Carvajal | Statement: [Jorge Carvajal (YouTube personality), familyName, Carvajal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carvajal Context triple: [Jorge Carvajal (YouTube personality), familyName, Carvajal]
-
A.
Carvajal
chosen
Carvajal is a Spanish surname of likely toponymic origin, borne by various notable figures in Spanish and Latin American history.
-
B.
Lorenzo Daza
Lorenzo Daza is a character in Gabriel García Márquez’s novel "Love in the Time of Cholera," known as the ambitious and socially aspiring father of Fermina Daza.
-
C.
Álvaro
Álvaro is a masculine given name of Spanish origin commonly used in Spain and Latin America.
-
D.
Javier
Javier is a masculine given name of Spanish origin commonly used in Spanish-speaking countries and beyond.
-
E.
Cerca-Carvajal
Cerca-Carvajal is a commune and town located in Haiti’s Centre Department.
- 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_69ca835811d8819081ea00fd2a2c9a1c |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d0791208190b043332247372d7b |
completed | March 31, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf516d9d9081909230441dd349dc9e |
completed | April 3, 2026, 5:34 a.m. |
Created at: March 30, 2026, 6:36 p.m.