Triple
T24312054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chicago street network |
E612700
|
entity |
| Predicate | hasZeroPoint |
P65427
|
FINISHED |
| Object | intersection of State Street and Madison Street |
—
|
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: intersection of State Street and Madison Street | Statement: [Chicago street network, hasZeroPoint, intersection of State Street and Madison Street]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasZeroPoint Context triple: [Chicago street network, hasZeroPoint, intersection of State Street and Madison Street]
-
A.
isZeroFor
Indicates that a given value, expression, or function evaluates to zero when applied to or considered with respect to a specified entity or context.
-
B.
hasIndependentDigitZero
Indicates that an entity possesses at least one digit or numeral component that is a zero considered as a distinct, standalone element.
-
C.
formsZeroPointFor
chosen
Indicates that one entity serves as the reference or origin point (zero point) for measuring or defining another entity.
-
D.
hasKPoint
Indicates that an entity possesses or is associated with a specific K-point, typically a designated point in reciprocal or parameter space.
-
E.
hasNumberOfPoints
Indicates that an entity is associated with a specific count of points it possesses or comprises.
- 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_69e2d7d91bb48190bc5377d17a85fb21 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2922b867c8190a6bf2adbfb68a584 |
completed | April 29, 2026, 11:20 p.m. |
| PD | Predicate disambiguation | batch_69f1c45f45888190a9ccc225906c34bd |
completed | April 29, 2026, 8:42 a.m. |
Created at: April 18, 2026, 1:43 a.m.