Triple
T7379976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | José Gregorio Argomedo |
E170221
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Argomedo |
E170221
|
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: Argomedo | Statement: [José Gregorio Argomedo, familyName, Argomedo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Argomedo Context triple: [José Gregorio Argomedo, familyName, Argomedo]
-
A.
Argomedo
chosen
Argomedo is a Spanish-language surname most notably associated with Chilean lawyer and politician José Gregorio Argomedo.
-
B.
Pasochoa
Pasochoa is an extinct volcanic mountain in Ecuador known for its lush cloud forests and rich biodiversity within a protected ecological reserve.
-
C.
Oteiza
Oteiza is a Basque surname most notably associated with the Spanish sculptor and artist Jorge Oteiza.
-
D.
Andalgalá
Andalgalá is a town in northwestern Argentina known for its mining activities and scenic location in the foothills of the Andes within Catamarca Province.
-
E.
Unzaga
Unzaga is a Spanish surname historically associated with families of Basque origin and notable figures in Spain and Latin America.
- 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_69c68a5d0ed08190b6d361e68f813330 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f1c61484819087874d4e7f9fd791 |
completed | March 27, 2026, 9:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c802d86da48190a1311c5c52a5f296 |
completed | March 28, 2026, 4:33 p.m. |
Created at: March 27, 2026, 3:08 p.m.