Triple
T814627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unity Cemetery, Latrobe, Pennsylvania, United States |
E17623
|
entity |
| Predicate | hasTypeOfGraveMarkers |
P11281
|
FINISHED |
| Object | headstones |
—
|
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: headstones | Statement: [Unity Cemetery, Latrobe, Pennsylvania, United States, hasTypeOfGraveMarkers, headstones]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfGraveMarkers Context triple: [Unity Cemetery, Latrobe, Pennsylvania, United States, hasTypeOfGraveMarkers, headstones]
-
A.
hasTypeOfBurial
Indicates the specific kind or method of burial associated with an entity.
-
B.
hasGravestoneStyle
chosen
Indicates that an entity’s gravestone is characterized by or associated with a particular style or design.
-
C.
hasCemeteryType
Indicates that a cemetery is classified as belonging to a specific type or category of cemetery.
-
D.
cemeteryType
Indicates the specific kind or classification of a cemetery associated with an entity.
-
E.
hasMausoleum
Indicates that one entity possesses, contains, or is associated with a mausoleum dedicated to another entity.
- 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_69a4937bcaac8190a322524ac6f45a5a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ab5035608190bff5f3843b75e662 |
completed | March 1, 2026, 9:10 p.m. |
| PD | Predicate disambiguation | batch_69a4aa756920819080ae82948974c876 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.