Triple
T10709266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Line (Chicago "L") |
E252488
|
entity |
| Predicate | medianSection |
P95591
|
FINISHED |
| Object | Dan Ryan Expressway median |
—
|
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: Dan Ryan Expressway median | Statement: [Red Line (Chicago "L"), medianSection, Dan Ryan Expressway median]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: medianSection Context triple: [Red Line (Chicago "L"), medianSection, Dan Ryan Expressway median]
-
A.
medianType
Indicates the type or form of a median used in a given context, such as in statistics, geometry, or transportation.
-
B.
medianEquals
Indicates that the median value of a given set or sequence is equal to a specified value.
-
C.
middleRepresentative
Indicates that an entity serves as an intermediary or go-between representative connecting two other parties or sides.
-
D.
typicalSection
Indicates that one section is a standard, representative, or commonly occurring instance within a broader set or structure of sections.
-
E.
metBetween
Indicates that two or more entities had an in-person or virtual meeting or encounter with each other during a specified time or context.
- 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_69d6aa5cbabc8190973e683950d89faf |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fe5063bc8190ba12fd68a59c9a03 |
completed | April 9, 2026, 1:18 a.m. |
| PD | Predicate disambiguation | batch_69d6f30455888190b77f476b8418eaee |
completed | April 9, 2026, 12:29 a.m. |
| PDg | Predicate description generation | batch_69d6fa323564819097b207eb53f8a9b8 |
completed | April 9, 2026, 1 a.m. |
Created at: April 8, 2026, 9:13 p.m.