Triple
T33526687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Kiva |
E858657
|
entity |
| Predicate | hasInterpretiveUse |
P36768
|
FINISHED |
| Object | educational 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: educational exhibits | Statement: [Great Kiva, hasInterpretiveUse, educational exhibits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInterpretiveUse Context triple: [Great Kiva, hasInterpretiveUse, educational exhibits]
-
A.
hasInterpretiveElement
Indicates that something includes or is associated with an element involving interpretation, such as a subjective, analytical, or explanatory component.
-
B.
usedInInterpreting
Indicates that something serves as a basis, tool, or reference for understanding, explaining, or making sense of something else.
-
C.
hasExplicitInterpretation
Indicates that something is associated with a clearly defined and unambiguous meaning or interpretation.
-
D.
hasInterpretiveSigns
chosen
Indicates that interpretive or informational signs are present at or associated with the subject.
-
E.
hasInterpretiveGoal
Indicates that an entity is associated with a specific intended meaning, purpose, or objective guiding how something should be interpreted.
- 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_69f349781c6c819082c516b260efe7e2 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ffef812da48190b875a7376b24f92d |
completed | May 10, 2026, 2:37 a.m. |
| PD | Predicate disambiguation | batch_69ffedecd580819097851b1473fdd6ed |
completed | May 10, 2026, 2:31 a.m. |
Created at: May 1, 2026, 1:39 a.m.