Triple
T7450911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Javiera Carrera |
E172005
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Javiera |
E172005
|
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: Javiera | Statement: [Javiera Carrera, givenName, Javiera]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Javiera Context triple: [Javiera Carrera, givenName, Javiera]
-
A.
Fabiola
Fabiola is a given name of Latin origin, historically associated with saints and European royalty.
-
B.
Alejandra
Alejandra is the feminine given name corresponding to Alejandro, commonly used in Spanish-speaking cultures.
-
C.
Javiera Carrera
chosen
Javiera Carrera was a prominent Chilean patriot and political figure who played a key role in the country’s early independence movement.
-
D.
Sheyla
Sheyla is a feminine given name, typically considered a variant of Sheila or Shayla and used in various cultures.
-
E.
Ivana Baquero
Ivana Baquero is a Spanish actress best known for her acclaimed performance as the young protagonist in Guillermo del Toro’s dark fantasy 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_69c68a66554c8190add75c65942c0317 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f38c28e08190956766a5222fe720 |
completed | March 27, 2026, 9:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c827b54a4881909f800bf37990a297 |
completed | March 28, 2026, 7:10 p.m. |
Created at: March 27, 2026, 3:14 p.m.