Triple
T11098898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clebsch diagonal surface |
E262450
|
entity |
| Predicate | hasLinesConfiguration |
P4876
|
FINISHED |
| Object | 27 lines in classical cubic surface configuration |
—
|
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: 27 lines in classical cubic surface configuration | Statement: [Clebsch diagonal surface, hasLinesConfiguration, 27 lines in classical cubic surface configuration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLinesConfiguration Context triple: [Clebsch diagonal surface, hasLinesConfiguration, 27 lines in classical cubic surface configuration]
-
A.
hasLineStructure
Indicates that one entity possesses or exhibits a linear arrangement or organization of its components.
-
B.
hasNumberOfLines
chosen
Indicates the relationship that specifies how many lines are associated with a given entity.
-
C.
hasFastLines
Indicates that the subject possesses or is associated with lines that operate or move at a high speed.
-
D.
hasLineGroup
Indicates that one entity is associated with, or belongs to, a particular group or collection of lines.
-
E.
hasLineLength
Indicates that one entity has, is characterized by, or is associated with a specific line length value.
- 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.