Triple
T15437719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinese continental crust |
E369809
|
entity |
| Predicate | thinnerIn |
P83261
|
FINISHED |
| Object | eastern 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: eastern China | Statement: [Chinese continental crust, thinnerIn, eastern China]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thinnerIn Context triple: [Chinese continental crust, thinnerIn, eastern China]
-
A.
isThickenedWith
Indicates that one substance has been made more viscous or dense by adding another substance that serves as a thickening agent.
-
B.
inker
Indicates that one entity serves as the inker for another, typically applying ink to finalize or enhance an existing drawing or artwork.
-
C.
thickness
Indicates the measure of how deep or wide an object or layer is from one surface or side to its opposite.
-
D.
formulatedIn
Indicates that something was created, developed, or expressed within a particular context, place, or framework.
-
E.
thinai
chosen
Indicates that one entity is thinner or has less thickness than another entity.
- 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_69d85a19180081909925012fbf4e62a3 |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03edca064819081510bf303271062 |
completed | April 16, 2026, 1:43 a.m. |
| PD | Predicate disambiguation | batch_69ded28276f481908c2038bb301e57cf |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:21 a.m.