Triple
T24699127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spatter Cones area |
E611679
|
entity |
| Predicate | interpretiveMaterials |
P140123
|
FINISHED |
| Object | wayside exhibits |
—
|
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: wayside exhibits | Statement: [Spatter Cones area, interpretiveMaterials, wayside exhibits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: interpretiveMaterials Context triple: [Spatter Cones area, interpretiveMaterials, wayside exhibits]
-
A.
interpretiveInformation
Indicates that one entity provides explanatory or contextual information used to interpret, clarify, or make sense of another entity or its content.
-
B.
featuresInterpretationsOf
chosen
Indicates that one entity presents or includes interpretive representations, analyses, or renditions of another entity.
-
C.
interpretationFacility
Indicates that an entity serves as a facility or venue where interpretation (such as language or translation services) is provided or supported.
-
D.
articleInterpreted
Indicates that an article has been read and its meaning or content has been understood or explained by an interpreting entity.
-
E.
containsInterpretationOf
Indicates that one entity includes or embodies an interpretation or understanding of another entity.
- 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_69e2c4d76d148190b58ad612467149a5 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f422aee0408190899efe7e24ef2b40 |
completed | May 1, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69f420e92cc88190a803aecdae78a051 |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 3:22 a.m.