Triple
T25389344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Auditorium Theatre of Roosevelt University |
E636116
|
entity |
| Predicate | previousStreetName |
P168026
|
FINISHED |
| Object | 50 East Congress Parkway |
—
|
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: 50 East Congress Parkway | Statement: [Auditorium Theatre of Roosevelt University, previousStreetName, 50 East Congress Parkway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: previousStreetName Context triple: [Auditorium Theatre of Roosevelt University, previousStreetName, 50 East Congress Parkway]
-
A.
namedAfterStreet
Indicates that an entity’s name is derived from or taken in honor of a particular street.
-
B.
hasFormerStreetName
Indicates that an entity (such as a street or place) was previously known by a different street name.
-
C.
roadName
Indicates the specific name assigned to a road that identifies it within a transportation or address system.
-
D.
hasNearbyStreet
Indicates that one entity is located close to or adjacent to a street.
-
E.
hasStreet
Indicates that an entity is located on, associated with, or identified by a particular street.
- 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_69e75db263888190b77fff9e2827b9a2 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f673633d288190b52ceb9f8a057c44 |
completed | May 2, 2026, 9:57 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
| PDg | Predicate description generation | batch_69f67256d064819094be04fc1bbbc635 |
completed | May 2, 2026, 9:53 p.m. |
Created at: April 21, 2026, 1:49 p.m.