Triple
T23012133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | O Lago |
E572933
|
entity |
| Predicate | titleTranslation |
P38
|
FINISHED |
| Object | The Lake |
—
|
NE NERFINISHED |
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: The Lake | Statement: [O Lago, titleTranslation, The Lake]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Lake Context triple: [O Lago, titleTranslation, The Lake]
-
A.
The Lake
The Lake is a village-like neighborhood in Newton, Massachusetts, known for its strong community identity and historically Irish-American roots.
-
B.
The Lake
The Lake is a picturesque man-made body of water in New York City's Central Park, popular for boating, scenic views, and surrounding walking paths.
-
C.
The Lake
The Lake is a painting by British artist L. S. Lowry, known for his distinctive depictions of industrial landscapes and urban life.
-
D.
The Lake
"The Lake" is a film featuring actor Diarmaid Murtagh, known for his roles in various television series and movies.
-
E.
The Lakes
The Lakes is a British television drama series set in England’s Lake District, following the troubled life of a young man who relocates there seeking a fresh start.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
Provenance (2 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_69e245b764cc8190a51be76f1d9611e1 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f183e202a481908d7a2f00a12229a0 |
completed | April 29, 2026, 4:06 a.m. |
Created at: April 17, 2026, 3:51 p.m.