Triple
T5531164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benito Cereno |
E145049
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Babo |
E529013
|
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: Babo | Statement: [Benito Cereno, hasCharacter, Babo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Babo Context triple: [Benito Cereno, hasCharacter, Babo]
-
A.
Babo
chosen
Babo is a central character in Herman Melville’s novella "Benito Cereno," known as the cunning leader of a slave revolt who manipulates appearances aboard a Spanish slave ship.
-
B.
Bubi
Bubi is a Bantu language spoken by the Bubi people, primarily on Bioko Island in Equatorial Guinea.
-
C.
Bubi
Bubi is the nickname of Erich Hartmann, the German World War II fighter pilot who became history’s highest-scoring flying ace.
-
D.
Bebek
Bebek is an upscale seaside neighborhood on Istanbul’s Bosphorus shore, known for its scenic views, cafes, and vibrant social life.
-
E.
Babica
Babica is a mountain peak located in the Maków Beskids range in southern Poland.
- 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_69c008f9955881909bfa8348b56b4739 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f9b59bc8190a8758b3be54831e9 |
completed | March 22, 2026, 4:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04cdccb70819081bfe0e4a56f253f |
completed | March 22, 2026, 8:11 p.m. |
Created at: March 22, 2026, 3:34 p.m.