Triple
T5847808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huang Hai |
E129753
|
entity |
| Predicate | surfaceFreezing |
P4500
|
FINISHED |
| Object | partly freezes in winter in northern areas |
—
|
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: partly freezes in winter in northern areas | Statement: [Huang Hai, surfaceFreezing, partly freezes in winter in northern areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: surfaceFreezing Context triple: [Huang Hai, surfaceFreezing, partly freezes in winter in northern areas]
-
A.
surfaceFreezesPartiallyIn
chosen
Indicates that a surface undergoes a freezing process in which only part of it becomes frozen within a given medium, environment, or container.
-
B.
freezesOver
Indicates that a liquid surface becomes solid due to low temperatures, typically forming a layer of ice over it.
-
C.
hasIceSurface
Indicates that an entity possesses or is characterized by a surface composed primarily of ice.
-
D.
iceFeature
Indicates a relationship where a geographic or environmental feature is composed of, covered by, or characterized by ice.
-
E.
snowCover
Indicates that one entity is covered by or blanketed with snow.
- 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_69c0084bd31c8190a796bb6284845e83 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03c9239e08190bff7ef2bd6d21ae0 |
completed | March 22, 2026, 7:01 p.m. |
| PD | Predicate disambiguation | batch_69c0334412388190bc594794ec5754f9 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:55 p.m.