Triple
T18738168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexandra Cunningham |
E458219
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Bravo |
E65800
|
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: Bravo | Statement: [Alexandra Cunningham, employer, Bravo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bravo Context triple: [Alexandra Cunningham, employer, Bravo]
-
A.
Bravo
chosen
Bravo is an American cable television network best known for its reality TV programming and pop culture–focused entertainment.
-
B.
Bravo
Bravo is a company best known for operating the Bravo app, a platform that facilitates cashless tipping and payments.
-
C.
Brava
Brava is a small, mountainous island in the Cape Verde archipelago known for its lush vegetation, volcanic landscapes, and traditional Creole culture.
-
D.
Bravos
Bravos is the popular nickname of FC Juárez, a professional football club based in Ciudad Juárez, Mexico.
-
E.
Badge of Honour
The Badge of Honour is a Jamaican national award conferred on individuals for meritorious service and outstanding contributions to the country.
- 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_69d8d394dc308190b6725073f5db324c |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5768b80ac8190bc05628d64f86fc9 |
completed | April 20, 2026, 12:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a053261c074819081acb03dd7f8f62a |
completed | May 14, 2026, 2:24 a.m. |
Created at: April 10, 2026, 11:51 a.m.