Triple
T35707554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cyrillic Pe |
E1031758
|
entity |
| Predicate | similarInShapeTo |
P40719
|
FINISHED |
| Object | Greek Pi |
—
|
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: Greek Pi | Statement: [Cyrillic Pe, similarInShapeTo, Greek Pi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: similarInShapeTo Context triple: [Cyrillic Pe, similarInShapeTo, Greek Pi]
-
A.
materiallySimilarTo
Indicates that two entities share substantially the same physical or material characteristics, composition, or properties, though they may not be exactly identical.
-
B.
hasSimilarityTo
Indicates that one entity shares common characteristics, features, or qualities with another entity to a notable degree.
-
C.
lessSimilarTo
Indicates that one entity is considered to share fewer similarities or a weaker resemblance with another entity compared to some reference or alternative.
-
D.
shapeInfluencedBy
Indicates that the form or outline of one entity is affected, determined, or modified by another entity or factor.
-
E.
hasApproximateShape
chosen
Indicates that one entity has a shape that is similar to, but not exactly the same as, the shape of 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_69f76e0d393c8190b6303c64408736db |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a34f8ee08190a040304635539a8f |
completed | May 3, 2026, 7:34 p.m. |
| PD | Predicate disambiguation | batch_69f7a06f125c8190843af194f042a465 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:05 p.m.