Triple
T32440371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queens Chapel |
E828995
|
entity |
| Predicate | nearBoundary |
P144886
|
FINISHED |
| Object | Maryland state line |
—
|
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: Maryland state line | Statement: [Queens Chapel, nearBoundary, Maryland state line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearBoundary Context triple: [Queens Chapel, nearBoundary, Maryland state line]
-
A.
nearBorderBetween
Indicates that something is located close to the dividing line or boundary shared between two adjacent areas or regions.
-
B.
nearStateBorderWith
chosen
Indicates that one entity is located close to the state border shared with another specified state or region.
-
C.
nearBorderDirection
Indicates that one entity is located close to a border or boundary in a specified directional orientation relative to that border.
-
D.
nearInternationalBoundary
Indicates that one entity is located close to an international boundary separating two or more countries.
-
E.
near
Indicates that one entity is located at a short distance from another entity in space or position.
- 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_69f3491bf298819097b610f772d54a6d |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fda94697c4819081291967202248be |
completed | May 8, 2026, 9:13 a.m. |
| PD | Predicate disambiguation | batch_69fda5973fcc8190a57daef31fb70a49 |
completed | May 8, 2026, 8:57 a.m. |
Created at: May 1, 2026, 12:55 a.m.