Triple
T10634169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Herbert Von King Park |
E250534
|
entity |
| Predicate | typeOfLandmark |
P95089
|
FINISHED |
| Object | local landmark |
—
|
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: local landmark | Statement: [Herbert Von King Park, typeOfLandmark, local landmark]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfLandmark Context triple: [Herbert Von King Park, typeOfLandmark, local landmark]
-
A.
monumentType
Indicates the specific kind or category of monument that an entity is classified as.
-
B.
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.
-
C.
cityLandmarkID
Indicates that a specific landmark is uniquely identified as being located within a particular city.
-
D.
typeOfToponym
Indicates the specific category or kind of place name (toponym) that applies to a given geographic entity.
-
E.
hasTouristAttractionRole
Indicates that an entity serves in the capacity or function of a tourist attraction for another entity (such as a place, organization, or area).
- 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_69d6aa5993448190a493b790b8f85010 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6dfab47bc819086684edc1b6dce74 |
completed | April 8, 2026, 11:07 p.m. |
| PD | Predicate disambiguation | batch_69d6dd83b114819098e84dc658e82d7e |
completed | April 8, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69d6df463ea8819091d6683e476b4f21 |
completed | April 8, 2026, 11:05 p.m. |
Created at: April 8, 2026, 9:03 p.m.