Triple
T30792871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saukville |
E784144
|
entity |
| Predicate | hasBlendOfCharacter |
P170145
|
FINISHED |
| Object | rural |
—
|
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 | Statement: [Saukville, hasBlendOfCharacter, rural]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBlendOfCharacter Context triple: [Saukville, hasBlendOfCharacter, rural]
-
A.
hasBlendOf
Indicates that something is composed of or contains a mixture of multiple specified components or elements.
-
B.
isBlended
Indicates that one entity has been mixed or combined thoroughly with another (or others) to form a uniform whole.
-
C.
hasBlendOfOldAndNew
Indicates that something combines or integrates both traditional/older elements and modern/newer elements into a single whole.
-
D.
usedInBlends
Indicates that something serves as an ingredient or component within one or more mixtures, combinations, or blends.
-
E.
blendingRole
Indicates the specific function or contribution an entity has within a mixture or combination process.
- 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_69f224b2e2a48190b19aa43db9da5b67 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6900f50ec8190be2ee3c76edc8502 |
completed | May 3, 2026, midnight |
| PD | Predicate disambiguation | batch_69f686140aa08190a35f62572b2db9b6 |
completed | May 2, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69f68848ad348190a2fb6e841dcfdb7d |
completed | May 2, 2026, 11:27 p.m. |
Created at: April 29, 2026, 8:42 p.m.