Triple
T8616910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adair, Iowa |
E204060
|
entity |
| Predicate | hasRegionalCharacter |
P71987
|
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: [Adair, Iowa, hasRegionalCharacter, rural community]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegionalCharacter Context triple: [Adair, Iowa, hasRegionalCharacter, rural community]
-
A.
hasLocalCharacter
chosen
Indicates that something possesses qualities, features, or significance that are specific to a particular locality or region.
-
B.
hasLanguageCharacter
Indicates that an entity uses, contains, or is associated with a specific written or symbolic character from a language.
-
C.
hasSpecialCharacter
Indicates that a given entity (such as a string or identifier) contains at least one non-alphanumeric special character.
-
D.
hasUnicode
Indicates that an entity is associated with, represented by, or encoded using a specific Unicode character or sequence.
-
E.
hasUnicodeProperty
Indicates that an entity possesses a specific Unicode character property or set of properties (such as category, script, or other Unicode-defined attributes).
- 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_69ca832ceab8819096e4a9f546695079 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc4711c7748190af26ff5a78ef66a2 |
completed | March 31, 2026, 10:13 p.m. |
| PD | Predicate disambiguation | batch_69cc455437488190b7506f820daf6e32 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:25 p.m.