Triple
T4487063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Snake Alley Historic District |
E107265
|
entity |
| Predicate | hasCurveCount |
P51537
|
FINISHED |
| Object | multiple sharp curves |
—
|
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: multiple sharp curves | Statement: [Snake Alley Historic District, hasCurveCount, multiple sharp curves]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCurveCount Context triple: [Snake Alley Historic District, hasCurveCount, multiple sharp curves]
-
A.
numberOfCurves
chosen
Indicates the relationship that specifies how many distinct curves are associated with or contained in a given entity.
-
B.
isCurved
Indicates that an object or path deviates smoothly from a straight line, forming a bend or arc.
-
C.
hasNumberOfPoints
Indicates that an entity is associated with a specific count of points it possesses or comprises.
-
D.
hasMaximumGradeBeforeCurves
Indicates that an entity’s highest achievable grade is specified prior to any grading curves or adjustments being applied.
-
E.
hasNumberOfArches
Indicates the relationship specifying how many arches are present in or associated with a given 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_69bd43f84f788190a1383579c4a595be |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd556d29f08190bab1e872dd7e819f |
completed | March 20, 2026, 2:10 p.m. |
| PD | Predicate disambiguation | batch_69bd5213e3d0819094b026989e686f01 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 12:59 p.m.