Triple
T5149678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Angle |
E116161
|
entity |
| Predicate | hasInterpretiveMarkers |
P36768
|
FINISHED |
| Object | National Park Service interpretive signs |
—
|
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: National Park Service interpretive signs | Statement: [The Angle, hasInterpretiveMarkers, National Park Service interpretive signs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInterpretiveMarkers Context triple: [The Angle, hasInterpretiveMarkers, National Park Service interpretive signs]
-
A.
hasInterpretiveElement
Indicates that something includes or is associated with an element involving interpretation, such as a subjective, analytical, or explanatory component.
-
B.
hasInterpretiveSigns
chosen
Indicates that interpretive or informational signs are present at or associated with the subject.
-
C.
isInterpretedBy
Indicates that something (such as data, a work, or a signal) is given meaning, understanding, or explanation by a particular agent or process.
-
D.
containsInterpretationOf
Indicates that one entity includes or embodies an interpretation or understanding of another entity.
-
E.
hasMarker
Indicates that one entity possesses, is associated with, or is identified by a specific marker.
- 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_69bd4446c0e08190a7c29dc74976bf03 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd78d7f4d081908d59adcd86f52f1d |
completed | March 20, 2026, 4:42 p.m. |
| PD | Predicate disambiguation | batch_69bd77ae2f10819098bb8939106e1281 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:43 p.m.