Triple
T9900612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ward 5 of Washington, D.C. |
E182270
|
entity |
| Predicate | containsNeighborhood |
P4813
|
FINISHED |
| Object | Eckington |
E215620
|
NE 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: Eckington | Statement: [Ward 5 of Washington, D.C., containsNeighborhood, Eckington]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eckington Context triple: [Ward 5 of Washington, D.C., containsNeighborhood, Eckington]
-
A.
Eckington
Eckington is a village and civil parish in the county of Derbyshire, England, known for its historic buildings and semi-rural character near the border with South Yorkshire.
-
B.
Eckington
chosen
Eckington is a historic residential neighborhood in Washington, D.C., known for its rowhouses, proximity to downtown, and evolving urban character.
-
C.
Burleith
Burleith is a residential neighborhood in northwest Washington, D.C., known for its tree-lined streets and proximity to Georgetown and the Georgetown University campus.
-
D.
Lansdowne
Lansdowne is a small suburban borough in Delaware County, Pennsylvania, known for its historic homes and proximity to Philadelphia.
-
E.
Greenwood Yard
Greenwood Yard is a major maintenance and storage facility serving Toronto's subway system.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca82876f8081909cf75df0f99bb13f |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cdb4e0705c8190bd17e36aff615cdd |
completed | April 2, 2026, 12:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1eb2125208190b4cf549d67d1ca42 |
completed | April 5, 2026, 4:54 a.m. |
Created at: March 30, 2026, 8:40 p.m.