Triple
T16807243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Balmer series of hydrogen |
E408510
|
entity |
| Predicate | hasFirstLineUpperLevel |
P124925
|
FINISHED |
| Object | principal quantum number n = 3 |
—
|
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: principal quantum number n = 3 | Statement: [Balmer series of hydrogen, hasFirstLineUpperLevel, principal quantum number n = 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFirstLineUpperLevel Context triple: [Balmer series of hydrogen, hasFirstLineUpperLevel, principal quantum number n = 3]
-
A.
hasLowerLevelLine
Indicates that one line is positioned or ranked below another line within a hierarchical or layered structure.
-
B.
hasTopLevel
Indicates that one entity is the highest or primary element within a hierarchy or structure relative to another entity.
-
C.
hasUppercase
Indicates that an entity contains at least one uppercase (capital) letter.
-
D.
hasUpperCourseName
Indicates that an entity (such as a course instance or section) is associated with the name of the higher-level or parent course of which it is a part.
-
E.
hasInitialLetters
Indicates that one entity’s initial letters or acronym are derived from or correspond to the other entity.
- F. None of above. chosen
Provenance (4 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_69d88393905081908d00a86b99996ac8 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2cd1e8c8190a7a05ba255f711c7 |
completed | April 18, 2026, 4:35 p.m. |
| PD | Predicate disambiguation | batch_69e32b814b188190aee525f8779203cd |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e34fb7c8c8819086975b7955b7d8ef |
completed | April 18, 2026, 9:32 a.m. |
Created at: April 10, 2026, 5:22 a.m.