Triple
T1000549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diego Velázquez de Cuéllar |
E21592
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Diego |
E15778
|
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: Diego | Statement: [Diego Velázquez de Cuéllar, givenName, Diego]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Diego Context triple: [Diego Velázquez de Cuéllar, givenName, Diego]
-
A.
Diego
chosen
Diego is a given name of Spanish origin commonly used in Spanish-speaking countries and beyond.
-
B.
Sebastián
Sebastián is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
-
C.
Jorge
Jorge is the birth name of Pope Francis, the head of the Roman Catholic Church and the first pope from the Americas.
-
D.
Armando
Armando is a masculine given name of Spanish and Portuguese origin, commonly used in many Spanish-speaking countries.
-
E.
Raúl
Raúl 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_69a493c476b48190b41fc5e793171cc6 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4fb18b88190ae2d620aaaff4f90 |
completed | March 1, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac89f9d7688190836459b2453e5e2b |
completed | March 7, 2026, 8:26 p.m. |
Created at: March 1, 2026, 7:41 p.m.