Triple
T15371898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Davis |
E367567
|
entity |
| Predicate | featureDesignation |
P118490
|
FINISHED |
| Object | Pennsylvania state high point |
—
|
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: Pennsylvania state high point | Statement: [Mount Davis, featureDesignation, Pennsylvania state high point]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featureDesignation Context triple: [Mount Davis, featureDesignation, Pennsylvania state high point]
-
A.
featureType
Indicates the specific kind or category of feature that characterizes or distinguishes an entity.
-
B.
designedFeature
Indicates that one entity is a feature or component intentionally planned, created, or specified by another entity as part of a design.
-
C.
namedFeature
Indicates that an entity has a specific feature or attribute that is explicitly given a name.
-
D.
exampleDesignation
Indicates that one entity is identified or labeled as a representative or illustrative instance of another entity.
-
E.
mapDesignation
Indicates a formal label or identifier that is assigned to something specifically for use on a map.
- 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e5c1d548190930bfaf0861595ae |
completed | April 16, 2026, 1:41 a.m. |
| PD | Predicate disambiguation | batch_69ded27742a881909cd73cc5c7d062fd |
completed | April 14, 2026, 11:49 p.m. |
| PDg | Predicate description generation | batch_69ded57005608190886cd01f640dfedb |
completed | April 15, 2026, 12:01 a.m. |
Created at: April 10, 2026, 3:18 a.m.