Triple
T16897778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evergreen Cemetery, Chester, Illinois |
E424351
|
entity |
| Predicate | hasGravemarkersFromPeriod |
P87860
|
FINISHED |
| Object | 19th century |
—
|
LITERAL 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: 19th century | Statement: [Evergreen Cemetery, Chester, Illinois, hasGravemarkersFromPeriod, 19th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGravemarkersFromPeriod Context triple: [Evergreen Cemetery, Chester, Illinois, hasGravemarkersFromPeriod, 19th century]
-
A.
hasGraveMarkersFromPeriod
chosen
Indicates that an entity possesses grave markers that date from, or are associated with, a specified historical period.
-
B.
hasGraveMarkersMaterial
Indicates that the material composition of grave markers is a specified substance or type.
-
C.
hasHistoricMarker
Indicates that something is associated with or identified by an official historic marker or plaque recognizing its historical significance.
-
D.
hasLanguagePeriod
Indicates a relationship where a language is associated with a specific historical or temporal period during which it was used or recognized.
-
E.
hasMarker
Indicates that one entity possesses, is associated with, or is identified by a specific marker.
- F. None of above.
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_69d889da3e8c8190a2b118f383f0beac |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3c8d98c308190bcc0adc7797d1f40 |
completed | April 18, 2026, 6:09 p.m. |
| PD | Predicate disambiguation | batch_69e32b9489408190bcb2ede567ff5bf9 |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:29 a.m.