Triple
T30992645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Devil’s Bridge (Toome Hill) |
E789707
|
entity |
| Predicate | isPointOfInterest |
P13974
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Devil’s Bridge (Toome Hill), isPointOfInterest, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isPointOfInterest Context triple: [Devil’s Bridge (Toome Hill), isPointOfInterest, true]
-
A.
isLandmarkFor
Indicates that one entity serves as a notable or significant reference point or attraction for another entity, such as a place, route, or area.
-
B.
isSocialLandmark
Indicates that a place functions as a notable social gathering point or reference location within a community or area.
-
C.
featureOfInterest
Indicates the entity or object that is the primary subject or focus of the described observation, measurement, or analysis.
-
D.
isLocalLandmark
chosen
Indicates that something is recognized as a notable or significant landmark within a specific local area or community.
-
E.
isNonWalkingAttraction
Indicates that an attraction is not intended to be experienced primarily by walking, but instead through another mode (e.g., ride, seated show, or stationary experience).
- 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_69f224c550b081909ddfceb0c3d03bdd |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6953bafb88190a860e9c68a3dd4b2 |
completed | May 3, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69f690ef92308190903a54fc74233269 |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 29, 2026, 8:56 p.m.