Triple
T4142911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Danvers |
E89311
|
entity |
| Predicate | geographicalRegionType |
P54124
|
FINISHED |
| Object | urban community |
—
|
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: urban community | Statement: [South Danvers, geographicalRegionType, urban community]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: geographicalRegionType Context triple: [South Danvers, geographicalRegionType, urban community]
-
A.
countryRegion
Indicates that a country is located within, or belongs to, a specific geographic or administrative region.
-
B.
geopoliticalRegion
Indicates a relationship where an entity is a defined political or administrative geographic area, such as a country, state, province, or similar region.
-
C.
culturalRegion
Indicates that an entity is located in, associated with, or belongs to a specific cultural region or cultural area.
-
D.
worldRegion
Indicates that one entity is a geographic region that encompasses, contains, or is associated with the other entity within the world.
-
E.
populationRegion
Indicates that a specified population is located within or associated with a particular geographic region.
- F. None of above. chosen
Provenance (4 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_69aed95785788190ae75bcf0cd1cafdf |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af03a0f3408190adba7a8513bd3d12 |
completed | March 9, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69af018a54848190987f18c066c75068 |
completed | March 9, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69af039fb19c8190b20e62a3b3ad25c1 |
completed | March 9, 2026, 5:30 p.m. |
Created at: March 9, 2026, 3:43 p.m.