Triple
T21966027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belmont Avenue, Chicago |
E542457
|
entity |
| Predicate | hasApproximateAddressNumber |
P22067
|
FINISHED |
| Object | 3200 North in Chicago grid system |
—
|
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: 3200 North in Chicago grid system | Statement: [Belmont Avenue, Chicago, hasApproximateAddressNumber, 3200 North in Chicago grid system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateAddressNumber Context triple: [Belmont Avenue, Chicago, hasApproximateAddressNumber, 3200 North in Chicago grid system]
-
A.
hasAddress
Indicates that an entity is associated with a specific address or location.
-
B.
hasApproximateLocation
chosen
Indicates that an entity is associated with a location that is known only imprecisely or within a general area rather than an exact position.
-
C.
hasApproximateOrderNumber
Indicates that an entity is associated with a non-exact, estimated, or approximate order number in a sequence or ordering.
-
D.
serviceNumberApproximate
Indicates that one entity’s service number is approximately equal to, but not necessarily exactly the same as, another entity’s service number.
-
E.
hasApproximateCoordinates
Indicates that an entity is associated with location coordinates that are estimated or imprecise rather than exact.
- 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_69e0c47fab1081908dc74a6545dbb051 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1245aabf88190a44564e6eaaa94ce |
completed | April 28, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69e6f601f2188190893bcdde0cf58ad6 |
completed | April 21, 2026, 3:58 a.m. |
Created at: April 16, 2026, 8:01 p.m.