Triple
T8408353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rodrigo Messi |
E198558
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Rodrigo |
E177155
|
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: Rodrigo | Statement: [Rodrigo Messi, givenName, Rodrigo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rodrigo Context triple: [Rodrigo Messi, givenName, Rodrigo]
-
A.
Rodrigo
chosen
Rodrigo is a masculine given name of Spanish and Portuguese origin, derived from the Germanic name Roderick and commonly used across the Spanish-speaking world.
-
B.
Gerardo
Gerardo is a masculine given name of Germanic origin, commonly used in Spanish and Italian-speaking countries.
-
C.
Sebastián
Sebastián is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
-
D.
Enrique
Enrique is a Spanish given name equivalent to the English name Henry.
-
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_69ca8310df9c8190b25f16161cca3e41 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb8315a8a8819097f6da11b909b527 |
completed | March 31, 2026, 8:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce030dccf08190a70c0abf0bdcf244 |
completed | April 2, 2026, 5:47 a.m. |
Created at: March 30, 2026, 6:05 p.m.