Triple
T12653805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loma |
E302229
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object | Toma |
E302230
|
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: Toma | Statement: [Loma, alternativeName, Toma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Toma Context triple: [Loma, alternativeName, Toma]
-
A.
Toma
Toma is a traditional semi-hard cow’s milk cheese from Italy’s Piedmont region, known for its mild, buttery flavor and smooth, elastic texture.
-
B.
Toma
chosen
Toma is a major Mande language spoken primarily in Guinea and neighboring West African countries.
-
C.
Saca
Saca is a Spanish-language surname most notably associated with former Salvadoran president Antonio Saca.
-
D.
Tanto
Tanto was a former town in Hyōgo Prefecture, Japan, that later became part of the expanded city of Toyooka through municipal merger.
-
E.
Tomei
Tomei is the surname of American actress Marisa Tomei, known for her Academy Award–winning performance in "My Cousin Vinny" and numerous film and television roles.
- 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96160730c81909e1aa3efb51bf159 |
completed | April 10, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6688104d48190939933b93b7e60cc |
completed | May 2, 2026, 9:11 p.m. |
Created at: April 9, 2026, 5:18 p.m.