Triple
T10080656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McAdoo, Pennsylvania |
E213890
|
entity |
| Predicate | settlementCategory |
P87
|
FINISHED |
| Object | borough in Pennsylvania |
—
|
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: borough in Pennsylvania | Statement: [McAdoo, Pennsylvania, settlementCategory, borough in Pennsylvania]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settlementCategory Context triple: [McAdoo, Pennsylvania, settlementCategory, borough in Pennsylvania]
-
A.
settingCategory
Indicates the classification or type of context in which something is set or configured (e.g., grouping settings under a common category).
-
B.
category
chosen
Indicates that one entity is classified as a member or type within the grouping or class defined by another entity.
-
C.
categoryForPlanning
Indicates that something is assigned to a specific category used for organizing or structuring planning activities or processes.
-
D.
realEstateCategory
Indicates the classification of a property into a specific type or category within real estate (e.g., residential, commercial, industrial).
-
E.
coreCategory
Indicates that one entity is the primary or fundamental category to which another entity belongs or is classified under.
- 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_69ca839bf730819086900c323c9b8c95 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd032ef288190a961d266d9ecafbc |
completed | April 2, 2026, 2:10 a.m. |
| PD | Predicate disambiguation | batch_69cd4b97870481908f7a89df10d58a9e |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9 p.m.