Triple
T5843493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carlos Navarro Montoya |
E129649
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Carlos |
E55653
|
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: Carlos | Statement: [Carlos Navarro Montoya, givenName, Carlos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carlos Context triple: [Carlos Navarro Montoya, givenName, Carlos]
-
A.
Carlos
chosen
Carlos is a common Spanish given name widely used across Spanish-speaking countries and communities.
-
B.
Carlos
Carlos is a biographical political thriller miniseries about the life of Venezuelan revolutionary and terrorist Ilich Ramírez Sánchez, known as "Carlos the Jackal."
-
C.
Carlos V
Carlos V is the dynastic title claimed by Infante Carlos, Count of Molina, as the Carlist pretender to the Spanish throne in the 19th century.
-
D.
Manuel
Manuel is the hapless, linguistically challenged Spanish waiter from the British sitcom "Fawlty Towers," known for his comedic misunderstandings and clashes with Basil Fawlty.
-
E.
Manuel
Manuel was the given name of Manuel II, the last King of Portugal who reigned in the early 20th century.
- 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_69c0084bd31c8190a796bb6284845e83 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c034d9da0c8190970319d0dc2fc73f |
completed | March 22, 2026, 6:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c113464f7481909538a1f2ef05216c |
completed | March 23, 2026, 10:17 a.m. |
Created at: March 22, 2026, 3:54 p.m.