Triple
T10703070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Theophania |
E252326
|
entity |
| Predicate | shortForm |
P43
|
FINISHED |
| Object | Fania |
E840766
|
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: Fania | Statement: [Theophania, shortForm, Fania]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fania Context triple: [Theophania, shortForm, Fania]
-
A.
Fania
chosen
Fania is an Italian diminutive form of the female given name Stefania.
-
B.
Fania All-Stars
Fania All-Stars is a legendary salsa supergroup formed by New York’s Fania Records label, known for bringing together many of the genre’s most influential musicians and popularizing salsa worldwide in the 1970s.
-
C.
Dizzy Flores
Dizzy Flores is a prominent Mobile Infantry soldier and close companion of Johnny Rico in the military science fiction universe of Starship Troopers.
-
D.
Maceo
Maceo is a Spanish-origin surname notably associated with Cuban independence leader Antonio Maceo.
-
E.
Maceo
Maceo is a municipality in the Magdalena Medio subregion of the Antioquia Department in Colombia, known for its rural character and role in regional agriculture and mining.
- 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_69d6aa5cbabc8190973e683950d89faf |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fddd28d481908abc5c1d4e5a9f3e |
completed | April 9, 2026, 1:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d998f5cda081909932daa3c98f8b46 |
completed | April 11, 2026, 12:42 a.m. |
Created at: April 8, 2026, 9:12 p.m.