Triple
T340614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kirkland |
E6827
|
entity |
| Predicate | isDerivedFromToponym |
P9174
|
FINISHED |
| Object | land associated with a church |
—
|
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: land associated with a church | Statement: [Kirkland, isDerivedFromToponym, land associated with a church]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isDerivedFromToponym Context triple: [Kirkland, isDerivedFromToponym, land associated with a church]
-
A.
isToponymic
Indicates that something is related to or derived from a place name (a toponym).
-
B.
hasToponymicForm
chosen
Indicates that one entity is a toponymic (place-name-based) form or variant derived from another entity.
-
C.
hasDemonym
Indicates that one entity is the term (demonym) used to refer to the inhabitants or natives of another entity (typically a place).
-
D.
hasNameOrigin
Indicates that the origin or source of an entity’s name is specified by the related entity.
-
E.
hasMetropolitanAreaName
Indicates that an entity is associated with a metropolitan area identified by a specific name.
- 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_69a2e7951ba08190960e90823b5078f3 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eae4fcc08190bd4c2bf0149c8b50 |
completed | Feb. 28, 2026, 1:17 p.m. |
| PD | Predicate disambiguation | batch_69a2e95197fc8190820e8ebd0d7d27fa |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.