Triple
T24971826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spring Township, Pennsylvania |
E624910
|
entity |
| Predicate | isPrimaryCommercialAreaFor |
P127310
|
FINISHED |
| Object | Reading, Pennsylvania metropolitan area |
—
|
NE NERFINISHED |
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: Reading, Pennsylvania metropolitan area | Statement: [Spring Township, Pennsylvania, isPrimaryCommercialAreaFor, Reading, Pennsylvania metropolitan area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isPrimaryCommercialAreaFor Context triple: [Spring Township, Pennsylvania, isPrimaryCommercialAreaFor, Reading, Pennsylvania metropolitan area]
-
A.
isPrimaryCommercialAreaOf
chosen
Indicates that one area serves as the main center of commercial activity for another specified place or region.
-
B.
isInBusinessDistrict
Indicates that an entity is located within a designated business or commercial district area.
-
C.
hasPrimaryServiceArea
Indicates that an entity is associated with a main geographic or functional area in which it primarily provides its services.
-
D.
connectsToCommercialArea
Indicates that one location has a direct link, route, or access path to a commercial area.
-
E.
isCommercialFacility
Indicates that a facility is used primarily for commercial or business-related activities or services.
- 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_69e2ff24512481908e9a72315b8d0354 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f606c79ad081908369605f72e65ca6 |
completed | May 2, 2026, 2:14 p.m. |
| PD | Predicate disambiguation | batch_69f602ce79ec8190b8336c2b9de18ac7 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 18, 2026, 6:01 a.m.