Triple
T11488211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moonlight Mile |
E272335
|
entity |
| Predicate | series |
P1761
|
FINISHED |
| Object | Kenzie and Gennaro |
E872251
|
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: Kenzie and Gennaro | Statement: [Moonlight Mile, series, Kenzie and Gennaro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kenzie and Gennaro Context triple: [Moonlight Mile, series, Kenzie and Gennaro]
-
A.
Gennaro
chosen
Gennaro is the surname of Angie Gennaro, a fictional character from Dennis Lehane’s crime novels.
-
B.
Santino
Santino is a masculine given name of Italian origin, often associated with the actor and singer Santino Fontana.
-
C.
Giovinco
Giovinco is an Italian surname most prominently associated with professional footballer Sebastian Giovinco.
-
D.
Frankie Crosetti
Frankie Crosetti was an American Major League Baseball shortstop and longtime coach best known for his decades-long tenure with the New York Yankees.
-
E.
Zaza
Zaza is an Iranian ethnic group primarily inhabiting eastern Turkey, known for speaking the Zazaki language and maintaining distinct cultural traditions.
- 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_69d6aae1b09881909ce2ded3fa0c14fa |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d85a1fc9688190aacc2eed64229b79 |
completed | April 10, 2026, 2:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e68508d3ac8190888982eca2472919 |
completed | April 20, 2026, 7:56 p.m. |
Created at: April 8, 2026, 9:36 p.m.