Triple
T2639790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gage Park, Chicago |
E62835
|
entity |
| Predicate | hasCommunityAreaNumber |
P15629
|
FINISHED |
| Object | 63 |
—
|
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: 63 | Statement: [Gage Park, Chicago, hasCommunityAreaNumber, 63]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommunityAreaNumber Context triple: [Gage Park, Chicago, hasCommunityAreaNumber, 63]
-
A.
communityAreaNumber
chosen
Indicates the specific numbered community area to which an entity is assigned or associated.
-
B.
hasAreaCode
Indicates that a specified telephone area code is assigned to or associated with a particular geographic region, location, or phone service entity.
-
C.
hasNearbyCommunity
Indicates that one entity has another community located close to it in geographic or spatial terms.
-
D.
communityDistrictNumber
Indicates the specific community district identifier associated with an entity or location.
-
E.
hasCommunityIn
Indicates that a community is present, active, or established within a specified location, platform, or context.
- 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_69ab4c3f2dcc819082df80f5e032f690 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abd8fafad08190939b08558fea6abd |
completed | March 7, 2026, 7:51 a.m. |
| PD | Predicate disambiguation | batch_69abd812849881908f956845a80e0205 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:53 p.m.