Triple
T7267448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Filippo Zappata |
E161012
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | CANT |
E126935
|
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: CANT | Statement: [Filippo Zappata, employer, CANT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CANT Context triple: [Filippo Zappata, employer, CANT]
-
A.
CANT
chosen
CANT was an Italian aircraft manufacturer known for producing military and civilian seaplanes and bombers, particularly during the interwar and World War II periods.
-
B.
Canti
Canti is a celebrated collection of lyric poems by Italian Romantic poet Giacomo Leopardi, known for its philosophical depth and melancholic reflection on the human condition.
-
C.
Canta
Canta is a town in Peru that serves as the administrative and commercial center of Canta Province in the Lima Region.
-
D.
Cantate
Cantate is a choral-orchestral composition by Igor Markevitch that showcases his distinctive modernist style and intricate vocal writing.
-
E.
cantos
Cantos are the major divisions or sections of a long narrative or epic poem, similar to chapters in a novel.
- 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_69c6885181008190b419040e22939c7c |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eae7b2108190a6910f6655669db5 |
completed | March 27, 2026, 8:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7db1a58dc81908f4d129f682f4589 |
completed | March 28, 2026, 1:43 p.m. |
Created at: March 27, 2026, 2:58 p.m.