Triple
T30011744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Day |
E762480
|
entity |
| Predicate | hasNameOriginAssociationWith |
P175345
|
FINISHED |
| Object | Dayton, Nevada |
—
|
NE NERFINISHED |
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: Dayton, Nevada | Statement: [John Day, hasNameOriginAssociationWith, Dayton, Nevada]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNameOriginAssociationWith Context triple: [John Day, hasNameOriginAssociationWith, Dayton, Nevada]
-
A.
hasNameOrigin
Indicates that the origin or source of an entity’s name is specified by the related entity.
-
B.
hasNameEtymologyIn
Indicates that the origin or derivation of an entity’s name is based in, or traceable to, a specified source such as a language, place, or cultural context.
-
C.
originAssociatedWith
Indicates a relationship where an entity is connected to, derived from, or influenced by a particular origin, source, or point of beginning.
-
D.
hasNameOriginType
Indicates that there is a specific type or category describing the origin of an entity’s name.
-
E.
hasOnomasticRelation
chosen
Indicates that there is a relationship between entities based on names, naming patterns, or shared onomastic (name-related) features.
- 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_69f2246b0c84819094f1250b6a02d277 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69fd82ed2a4c81908bd7797fbd2e3d08 |
completed | May 8, 2026, 6:30 a.m. |
| PD | Predicate disambiguation | batch_69fd814cc10481908e4f8123d35a5d0c |
completed | May 8, 2026, 6:23 a.m. |
Created at: April 29, 2026, 6:44 p.m.