Triple
T5650384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madison Street |
E124491
|
entity |
| Predicate | formsZeroPointFor |
P65427
|
FINISHED |
| Object | north–south address numbers in Chicago |
—
|
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: north–south address numbers in Chicago | Statement: [Madison Street, formsZeroPointFor, north–south address numbers in Chicago]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formsZeroPointFor Context triple: [Madison Street, formsZeroPointFor, north–south address numbers in Chicago]
-
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.
zeroConcept
Indicates a conceptual or abstract entity that has no concrete instances or realizations in the given context.
-
C.
digitSymbolForZero
Indicates that something serves as the written digit symbol representing the numerical value zero.
-
D.
isNonzeroFor
Indicates that a given value, function, or quantity is not equal to zero under specified conditions or for specified inputs.
-
E.
formsWith
Indicates that one entity combines or associates with another to create or constitute a joint structure, group, or configuration.
- F. None of above. chosen
Provenance (4 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_69c00825df388190a58742fa9b1aa33d |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c022d4ca788190b20168b20cb1d030 |
completed | March 22, 2026, 5:11 p.m. |
| PD | Predicate disambiguation | batch_69c01b2274b48190b2ef57ed728f785c |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f0727bc8190b16e9a669c04b4dd |
completed | March 22, 2026, 4:55 p.m. |
Created at: March 22, 2026, 3:42 p.m.