Triple
T30576970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2016 Great Wall Marathon |
E778275
|
entity |
| Predicate | courseFeatures |
P170242
|
FINISHED |
| Object | sections of the Great Wall of China |
—
|
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: sections of the Great Wall of China | Statement: [2016 Great Wall Marathon, courseFeatures, sections of the Great Wall of China]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: courseFeatures Context triple: [2016 Great Wall Marathon, courseFeatures, sections of the Great Wall of China]
-
A.
courseIncludes
Indicates that a course contains or covers a particular component, such as a topic, module, lesson, or resource.
-
B.
courseSetupCharacteristic
Indicates a defining setup-related property or configuration aspect associated with a course.
-
C.
featuresInstitution
Indicates that one entity includes, presents, or highlights an institution as a notable component or participant.
-
D.
featuresIn
Indicates that an entity appears or plays a role within another entity, such as a person or element being included in a work, event, or context.
-
E.
courseShape
Indicates the geometric layout or configuration that defines the path or outline of a course.
- 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_69f2249f8c148190ae7eb3912cde112a |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68b121eac81909e90416207bc1157 |
completed | May 2, 2026, 11:38 p.m. |
| PD | Predicate disambiguation | batch_69f6860def1c81909d79e1f088c4b5e5 |
completed | May 2, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69f68a160374819084d720985f800dfc |
completed | May 2, 2026, 11:34 p.m. |
Created at: April 29, 2026, 8:22 p.m.