Triple
T4475444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gallery of Maps |
E99996
|
entity |
| Predicate | hasNumberOfPanels |
P40883
|
FINISHED |
| Object | 40 |
—
|
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: 40 | Statement: [Gallery of Maps, hasNumberOfPanels, 40]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfPanels Context triple: [Gallery of Maps, hasNumberOfPanels, 40]
-
A.
numberOfPanels
chosen
Indicates the total count of distinct panels associated with or contained within a given entity.
-
B.
hasPanel
Indicates that one entity includes, is equipped with, or is associated with a panel as a component or feature.
-
C.
hasNumberOfVocationalPanels
Indicates the relationship specifying how many vocational panels are associated with a given entity.
-
D.
hasPanelFormat
Indicates that something is associated with a particular panel layout or format used for its presentation or display.
-
E.
languagePanelCount
Indicates the number of language panels associated with or present in a given context or 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_69b34553cbe48190afa8ac1cac285b86 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35728ed508190ba0e882fa62d8848 |
completed | March 13, 2026, 12:15 a.m. |
| PD | Predicate disambiguation | batch_69b3563d63008190816e37027e761375 |
completed | March 13, 2026, 12:11 a.m. |
Created at: March 12, 2026, 11:35 p.m.