Triple
T690626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Dupont Circle Building |
E13382
|
entity |
| Predicate | isIntersectionLandmark |
P15085
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [The Dupont Circle Building, isIntersectionLandmark, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isIntersectionLandmark Context triple: [The Dupont Circle Building, isIntersectionLandmark, true]
-
A.
isLocalLandmark
Indicates that something is recognized as a notable or significant landmark within a specific local area or community.
-
B.
hasNotableIntersection
Indicates that two entities intersect or cross at a point that is considered significant or noteworthy in some context.
-
C.
locatedAtIntersectionOf
chosen
Indicates that something is situated at the point where two or more paths, roads, or boundaries cross or meet.
-
D.
hasLandmarkOnBank
Indicates that a landmark is located on the bank (shore or edge) of a geographic feature such as a river, lake, or canal.
-
E.
fieldIntersection
Indicates that two or more fields or domains share a common overlapping area or set of elements.
- 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_69a4933e0f98819097d22766c49b61b8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a0ad379c81909003d35c63822780 |
completed | March 1, 2026, 8:25 p.m. |
| PD | Predicate disambiguation | batch_69a49d221d38819083c0adda81f59b07 |
completed | March 1, 2026, 8:10 p.m. |
Created at: March 1, 2026, 7:36 p.m.