Triple
T1337259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golden City R-III School District |
E28780
|
entity |
| Predicate | hasServiceAreaCharacteristic |
P3938
|
FINISHED |
| Object | rural 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: rural community | Statement: [Golden City R-III School District, hasServiceAreaCharacteristic, rural community]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasServiceAreaCharacteristic Context triple: [Golden City R-III School District, hasServiceAreaCharacteristic, rural community]
-
A.
serviceAreaCharacteristic
chosen
Indicates a relationship where a service area is associated with a specific attribute or feature that characterizes it.
-
B.
hasServiceAreas
Indicates that an entity provides services within, or is operational across, specific geographic or functional areas.
-
C.
areaServed
Indicates the geographic region or jurisdiction within which a service, organization, or activity is provided or applicable.
-
D.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
E.
sectorServed
Indicates the industry or economic sector that an entity primarily serves or targets with its activities, products, 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_69a498561a508190a3e1bc137c2b866a |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1edda1c81909a1149b254b0d57e |
completed | March 1, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69a4bef174708190a07bbc697fe19a2d |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:55 p.m.