Triple
T1280175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princess Christina of the Netherlands |
E27306
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Nicolas Guillermo |
E164397
|
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: Nicolas Guillermo | Statement: [Princess Christina of the Netherlands, child, Nicolas Guillermo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nicolas Guillermo Context triple: [Princess Christina of the Netherlands, child, Nicolas Guillermo]
-
A.
Jorge Guillermo
chosen
Jorge Guillermo is a Cuban-born American educator and former husband of Princess Christina of the Netherlands.
-
B.
Julián Felipe
Julián Felipe was a Filipino composer best known for writing the music of the Philippine national anthem.
-
C.
Nicolás
Nicolás is a masculine given name of Greek origin, commonly used in Spanish-speaking countries and derived from the name Nicholas, meaning "victory of the people."
-
D.
Jorge
Jorge is the birth name of Pope Francis, the head of the Roman Catholic Church and the first pope from the Americas.
-
E.
Sebastián
Sebastián 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_69a496d3710c8190955dee8bc0dacb50 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c094eb4881909a33061339f91190 |
completed | March 1, 2026, 10:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad08a3865c819093a6ffd1a8c74e2e |
completed | March 8, 2026, 5:26 a.m. |
Created at: March 1, 2026, 7:50 p.m.