Triple
T3290488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ariel |
E69087
|
entity |
| Predicate | torments |
P20070
|
FINISHED |
| Object | Antonio |
E56351
|
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: Antonio | Statement: [Ariel, torments, Antonio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Antonio Context triple: [Ariel, torments, Antonio]
-
A.
Antonio
chosen
Antonio is a masculine given name of Latin origin, widely used in Italian, Spanish, and Portuguese-speaking cultures.
-
B.
Antonio Vandone di Cortemilia
Antonio Vandone di Cortemilia was an Italian architect known for designing the Mogadishu Cathedral in Somalia during the colonial era.
-
C.
Lorenzo
Lorenzo is a masculine given name of Italian origin, historically borne by notable figures such as the Renaissance humanist Lorenzo Valla.
-
D.
Bernardo Morando
Bernardo Morando was a 16th-century Italian architect best known for designing the Renaissance ideal city of Zamość in Poland.
-
E.
Gonzalo
Gonzalo is a masculine given name of Spanish origin, historically borne by notable figures such as conquistadors, nobles, and literary characters.
- 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_69ad859d45748190b0742408c954b39f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb05bd6b08190bcb9f0e5da82bc21 |
completed | March 8, 2026, 5:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2e8654e8481908f4a8efa219edc54 |
completed | March 12, 2026, 4:23 p.m. |
Created at: March 8, 2026, 3:10 p.m.