Triple
T11098698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fano plane |
E262444
|
entity |
| Predicate | hasDualStructure |
P31337
|
FINISHED |
| Object | isomorphic to itself |
—
|
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: isomorphic to itself | Statement: [Fano plane, hasDualStructure, isomorphic to itself]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDualStructure Context triple: [Fano plane, hasDualStructure, isomorphic to itself]
-
A.
hasTwoPartStructure
Indicates that something is composed of exactly two distinct, structured parts that together form a whole.
-
B.
haveDualityProperty
chosen
Indicates that an entity possesses a characteristic or state that inherently consists of two complementary, contrasting, or coexisting aspects.
-
C.
hasTwinStructureWith
Indicates that two entities share an identical or nearly identical structural form, typically as corresponding or mirrored counterparts.
-
D.
hasHumanStructure
Indicates that one entity possesses or exhibits a structural form or organization characteristic of humans.
-
E.
hasTwinFeature
Indicates that two entities share an identical or nearly identical feature, characteristic, or component, as if they are twins in that respect.
- 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_69d6aa9a40d88190a373e2c7e48285db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79a0c46308190889b94c23ebaca62 |
completed | April 9, 2026, 12:22 p.m. |
| PD | Predicate disambiguation | batch_69d7441aa3548190b92dbde57841c135 |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:27 p.m.