Triple
T15008101
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ricardo Arjona |
E377760
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Arjona |
E379148
|
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: Arjona | Statement: [Ricardo Arjona, familyName, Arjona]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arjona Context triple: [Ricardo Arjona, familyName, Arjona]
-
A.
Arjona
chosen
Arjona is a Spanish-origin surname shared by various notable individuals in fields such as entertainment, sports, and the arts.
-
B.
Arnalta
Arnalta is a comic nurse character in Claudio Monteverdi’s opera "L'incoronazione di Poppea," known for her earthy wisdom and humorous commentary.
-
C.
Ayubia
Ayubia is a popular hill resort and national park area in Pakistan’s Galyat region, known for its cool climate, pine forests, and scenic chairlift.
-
D.
Ardolino
Ardolino is an Italian surname most notably associated with Emile Ardolino, the American film director and producer known for works like "Dirty Dancing."
-
E.
Soroa
Soroa is a small Cuban village and popular ecotourism destination known for its lush mountain scenery, waterfalls, and orchid garden.
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded73348d4819091d9e7f1b0fed822 |
completed | April 15, 2026, 12:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9dce8240819097efddb43b79ad4b |
completed | May 9, 2026, 2:37 a.m. |
Created at: April 10, 2026, 2:55 a.m.