Triple
T8998067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M. C. Escher |
E214968
|
entity |
| Predicate | placeOfDeath |
P21
|
FINISHED |
| Object | Laren |
E636603
|
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: Laren | Statement: [M. C. Escher, placeOfDeath, Laren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laren Context triple: [M. C. Escher, placeOfDeath, Laren]
-
A.
Laren
chosen
Laren is a historic and affluent village in the Dutch province of North Holland, known for its art colony heritage and picturesque residential character.
-
B.
Groveland
Groveland is a small unincorporated community in California’s Sierra Nevada foothills, known as a gateway town for visitors traveling to Yosemite National Park.
-
C.
Fairlawn
Fairlawn is a residential neighborhood and community within the city of Pawtucket in Providence County, Rhode Island.
-
D.
Barrington
Barrington is a small town located in Yates County in the Finger Lakes region of New York State.
-
E.
Barrington
Barrington is a suburban coastal town in Bristol County, Rhode Island, known for its affluent residential character and highly ranked public schools.
- 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_69ca83a05c608190bdfdbdb25e994b39 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc68e23734819083a98f4ff0942479 |
completed | April 1, 2026, 12:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfd0d586c881909090b424f6fd036f |
completed | April 3, 2026, 2:38 p.m. |
Created at: March 30, 2026, 7:05 p.m.