Triple
T37139628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carp Lake Township |
E920068
|
entity |
| Predicate | hasLowUrbanDevelopment |
P87091
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Carp Lake Township, hasLowUrbanDevelopment, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLowUrbanDevelopment Context triple: [Carp Lake Township, hasLowUrbanDevelopment, true]
-
A.
isLessUrbanizedThan
Indicates that one place has a lower degree of urban development or urban characteristics compared to another place.
-
B.
hasLowPopulationDensity
Indicates that the number of individuals or entities per unit area in a given region is relatively small compared to typical or expected levels.
-
C.
hasNoUrbanSettlement
Indicates that the referenced area or region does not contain any urban settlements such as towns or cities.
-
D.
isLargelyUndeveloped
chosen
Indicates that something has not been significantly developed, improved, or built up, remaining mostly in its original or primitive state.
-
E.
isLowland
Indicates that an entity is located in, associated with, or characteristic of lowland areas or low-lying terrain relative to surrounding regions.
- 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_69f76e9e9d008190a250b0387c992c74 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ff7c96e6dc8190b89554480ebcea39 |
completed | May 9, 2026, 6:27 p.m. |
| PD | Predicate disambiguation | batch_69ff7c2381748190ad9a2176e0e478cd |
completed | May 9, 2026, 6:25 p.m. |
Created at: May 3, 2026, 4:15 p.m.