Triple
T110515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woodlawn Cemetery, Elmira, New York, United States |
E2237
|
entity |
| Predicate | hasLandscapeType |
P7342
|
FINISHED |
| Object | lawn cemetery |
—
|
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: lawn cemetery | Statement: [Woodlawn Cemetery, Elmira, New York, United States, hasLandscapeType, lawn cemetery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandscapeType Context triple: [Woodlawn Cemetery, Elmira, New York, United States, hasLandscapeType, lawn cemetery]
-
A.
hasDiverseLandscape
Indicates that an entity possesses a variety of distinct physical or environmental features within its geographic area.
-
B.
hasLiftType
Indicates the specific type or category of lift associated with an entity.
-
C.
hasNumberOfScreens
Indicates the quantity of screens associated with or contained in a given entity.
-
D.
hasLandform
Indicates that one entity possesses, contains, or is characterized by a particular natural landform.
-
E.
hasPlatformType
Indicates that an entity is associated with or characterized by a specific type or category of platform.
- F. None of above. chosen
Provenance (4 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_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a258b58efc8190959c86f73d67b744 |
completed | Feb. 28, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69a25641058c8190b5b64509b35d8176 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a258b30f6c8190be2181f30c40e04d |
completed | Feb. 28, 2026, 2:53 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.