Triple
T22123777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastern Avenue NE |
E546739
|
entity |
| Predicate | separatesNeighborhoodFromState |
P147081
|
FINISHED |
| Object | Deanwood – Maryland |
—
|
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: Deanwood – Maryland | Statement: [Eastern Avenue NE, separatesNeighborhoodFromState, Deanwood – Maryland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: separatesNeighborhoodFromState Context triple: [Eastern Avenue NE, separatesNeighborhoodFromState, Deanwood – Maryland]
-
A.
separatesState
Indicates that one entity serves as a dividing boundary or barrier between two distinct states or regions.
-
B.
hasStateSubdivisionName
Indicates that an entity has a specific name for one of its internal state-level subdivisions.
-
C.
USStateSubdivision
Indicates that one entity is an administrative subdivision (such as a county, parish, or borough) within a U.S. state represented by the other entity.
-
D.
geographicallySeparatedDistrictOf
Indicates that one district is a non-contiguous, physically separate part of another district or administrative area.
-
E.
stateSubdivisionContext
Indicates the contextual relationship between a state and its internal administrative or territorial subdivisions.
- 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_69e11e39bf348190b541bfa16a7b71e0 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1298016e081909d00015ca516d9fd |
completed | April 28, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69e71b2ed7348190b6fa2e52f54393fb |
completed | April 21, 2026, 6:37 a.m. |
| PDg | Predicate description generation | batch_69e7222d208c819098b12c13e31af629 |
completed | April 21, 2026, 7:07 a.m. |
Created at: April 16, 2026, 8:31 p.m.