Triple
T26204655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frenchman’s Creek |
E655327
|
entity |
| Predicate | featuresSettingElement |
P32516
|
FINISHED |
| Object | Cornish creek |
—
|
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: Cornish creek | Statement: [Frenchman’s Creek, featuresSettingElement, Cornish creek]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresSettingElement Context triple: [Frenchman’s Creek, featuresSettingElement, Cornish creek]
-
A.
featuresSetting
chosen
Indicates that something includes, presents, or highlights a particular setting as a notable or primary aspect.
-
B.
featureSet
Indicates that one entity is a collection or configuration of features associated with or applied to another entity.
-
C.
featuresMode
Indicates that one entity operates in, supports, or is characterized by a particular mode or configuration specified by another entity.
-
D.
featuresElementSystem
Indicates that a system includes or incorporates a particular element as one of its constituent parts or components.
-
E.
featuresRecurringElement
Indicates that something includes an element, motif, or component that appears repeatedly over time or across multiple instances.
- 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_69ee5b49adb4819086545280d4ef6337 |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f7aa699d68819081ed363931894ab3 |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8cec6d48190bebfa884b2f938c0 |
completed | May 3, 2026, 7:58 p.m. |
Created at: April 26, 2026, 8:50 p.m.