Triple
T28200736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chita Peninsula |
E716876
|
entity |
| Predicate | helpsEnclose |
P164210
|
FINISHED |
| Object | Ise Bay |
—
|
NE NERFINISHED |
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: Ise Bay | Statement: [Chita Peninsula, helpsEnclose, Ise Bay]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: helpsEnclose Context triple: [Chita Peninsula, helpsEnclose, Ise Bay]
-
A.
enclosesArea
Indicates that one entity surrounds and contains a bounded region of space occupied or defined by another.
-
B.
hasEnclosures
Indicates that an entity possesses or contains one or more enclosing structures, spaces, or bounded areas associated with it.
-
C.
enclosedSince
Indicates that one entity has been contained or surrounded by another entity continuously starting from a specified point in time.
-
D.
closingContains
Indicates that one closing element, event, or period fully includes another within its temporal or structural bounds.
-
E.
helpsIn
Indicates that one entity provides assistance, support, or aid to another entity in performing or achieving a particular task, activity, or goal.
- 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_69efd6b826908190857e6e7dad74ed93 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f643c204508190a43fe0ec5165b01c |
completed | May 2, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69f641e0fde08190bf06a1c5b388aa84 |
completed | May 2, 2026, 6:26 p.m. |
| PDg | Predicate description generation | batch_69f6430975b481909191219ad13ef77e |
completed | May 2, 2026, 6:31 p.m. |
Created at: April 27, 2026, 10:31 p.m.