Triple
T5700882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gettysburg micropolitan area |
E125656
|
entity |
| Predicate | urbanCenterType |
P11334
|
FINISHED |
| Object | small town |
—
|
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: small town | Statement: [Gettysburg micropolitan area, urbanCenterType, small town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: urbanCenterType Context triple: [Gettysburg micropolitan area, urbanCenterType, small town]
-
A.
notableCityCenter
Indicates that a location serves as a prominent or significant central area within a city.
-
B.
hasPopulationCenterType
chosen
Indicates the classification of a population center by its type, such as city, town, village, or other settlement category.
-
C.
isDowntownCoreOf
Indicates that a location constitutes the central, most urbanized and commercially dense area of a larger city or metropolitan region.
-
D.
urbanAreaType
Indicates the classification of an area based on its urban characteristics or development type (e.g., city, town, suburb, metropolitan region).
-
E.
isUrbanCenter
Indicates that a place functions as a primary, densely developed hub of population, services, and activities within a region.
- 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_69c0082c96988190b3a6a201edce472a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c024540afc8190aee3760f71ea39c2 |
completed | March 22, 2026, 5:18 p.m. |
| PD | Predicate disambiguation | batch_69c021c2d8bc8190b947c7d1f423d2f3 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:45 p.m.