Triple
T8780878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rhode Island Avenue NW |
E208721
|
entity |
| Predicate | hasIntersectionPattern |
P8151
|
FINISHED |
| Object | diagonal across orthogonal grid |
—
|
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: diagonal across orthogonal grid | Statement: [Rhode Island Avenue NW, hasIntersectionPattern, diagonal across orthogonal grid]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIntersectionPattern Context triple: [Rhode Island Avenue NW, hasIntersectionPattern, diagonal across orthogonal grid]
-
A.
hasPattern
chosen
Indicates that one entity exhibits, follows, or is characterized by a specific recurring form, structure, or design defined by another entity.
-
B.
hasNotableIntersection
Indicates that two entities intersect or cross at a point that is considered significant or noteworthy in some context.
-
C.
hasUsePattern
Indicates a characteristic or recurring way in which something is typically used or applied.
-
D.
overlapsWith
Indicates that two entities share a common part or region in space, time, or extent, but neither is completely contained within the other.
-
E.
hasJunctionIn
Indicates that one entity contains or includes a junction located within the spatial or structural extent of another entity.
- 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_69ca835fbee88190bf625939bac48d7f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f55b7b08190ab3e18cd634a144b |
completed | March 31, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1aff3881908be6a9cbc9f50461 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:42 p.m.