Triple
T6038251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Javier Navarro |
E134475
|
entity |
| Predicate | canBeShortenedTo |
P32259
|
FINISHED |
| Object | Javi |
E214093
|
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: Javi | Statement: [Javier Navarro, canBeShortenedTo, Javi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Javi Context triple: [Javier Navarro, canBeShortenedTo, Javi]
-
A.
Javier
chosen
Javier is a masculine given name of Spanish origin commonly used in Spanish-speaking countries and beyond.
-
B.
Rubén
Rubén is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
-
C.
Álvaro
Álvaro is a masculine given name of Spanish origin commonly used in Spain and Latin America.
-
D.
Carvajal
Carvajal is a Spanish surname of likely toponymic origin, borne by various notable figures in Spanish and Latin American history.
-
E.
Pablo Adán
Pablo Adán is a Spanish voice actor best known for dubbing the character of the Faun in the film "Pan's Labyrinth."
- 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_69c00875db5c819099dd5bb833ec43c2 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056ccac948190a27547878d4db8e4 |
completed | March 22, 2026, 8:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c11cfbb4cc81909736d5d041dd0b23 |
completed | March 23, 2026, 10:59 a.m. |
Created at: March 22, 2026, 4:08 p.m.