Triple
T150896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lord Byron |
E3427
|
entity |
| Predicate | residence |
P75
|
FINISHED |
| Object | Venice |
E21687
|
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: Venice | Statement: [Lord Byron, residence, Venice]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Venice Context triple: [Lord Byron, residence, Venice]
-
A.
Venice
Venice is a vibrant beachfront neighborhood on Los Angeles’s Westside known for its bohemian spirit, canals, boardwalk, and skate and surf culture.
-
B.
Venice
chosen
Venice is a historic Italian city built on a network of canals in a lagoon of the Adriatic Sea, renowned for its unique architecture, art, and maritime heritage.
-
C.
Genoa
Genoa is a historic port city in northwestern Italy known for its significant maritime heritage, trade, and role as a major economic hub on the Ligurian coast.
-
D.
Milan
Milan is a major Italian metropolis renowned as a global center for fashion, design, finance, and culture.
-
E.
Florence
Florence is the birth name of Elizabeth Arden, the pioneering Canadian-American businesswoman who founded the iconic Elizabeth Arden cosmetics brand.
- 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a2580dda148190a522e0ac276d5f33 |
completed | Feb. 28, 2026, 2:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3232bf59c8190a8f2478c85b92ac8 |
completed | Feb. 28, 2026, 5:17 p.m. |
Created at: Feb. 28, 2026, 2:31 a.m.