Triple
T25530251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alaid |
E639890
|
entity |
| Predicate | shapeComparison |
P87414
|
FINISHED |
| Object | often compared to Mount Fuji for symmetry |
—
|
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: often compared to Mount Fuji for symmetry | Statement: [Alaid, shapeComparison, often compared to Mount Fuji for symmetry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shapeComparison Context triple: [Alaid, shapeComparison, often compared to Mount Fuji for symmetry]
-
A.
morphologicalComparison
chosen
Indicates a relationship where two or more entities are compared based on differences or similarities in their morphological (form or structural) characteristics.
-
B.
scaleComparison
Indicates a relationship where two or more entities are compared in terms of their size, magnitude, or scale relative to one another.
-
C.
faceResemblance
Indicates that one entity’s facial appearance is similar to or resembles that of another entity.
-
D.
hasSimilarityTo
Indicates that one entity shares common characteristics, features, or qualities with another entity to a notable degree.
-
E.
comparisonType
Indicates the specific kind of comparison being made between two or more values or entities (e.g., equality, inequality, ordering, or similarity).
- 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_69e75dbf3f9c8190b3f2a75d1b75d127 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f862f7ac819085591f517a266a1a |
completed | May 2, 2026, 1:13 p.m. |
| PD | Predicate disambiguation | batch_69f480789be08190ab252a6de3797200 |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 3:13 p.m.