Triple
T18371219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Verdet constant |
E446183
|
entity |
| Predicate | isTabulatedFor |
P56835
|
FINISHED |
| Object | common optical glasses |
—
|
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: common optical glasses | Statement: [Verdet constant, isTabulatedFor, common optical glasses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isTabulatedFor Context triple: [Verdet constant, isTabulatedFor, common optical glasses]
-
A.
isTabulatedBy
chosen
Indicates that data, values, or information are organized, arranged, or recorded in a table by a specified agent or process.
-
B.
hasTab
Indicates that one entity includes, contains, or is associated with a tab element or tabbed section related to another entity.
-
C.
hasTables
Indicates that an entity possesses or contains one or more tables.
-
D.
isInterpretableIn
Indicates that one formal system, language, or theory can be meaningfully represented, understood, or given a semantics within another system, language, or theory.
-
E.
tableType
Indicates the specific category or kind of table that an entity is classified as.
- 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_69d8b9f370b88190b1e5081c2c238e7f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e5175324e48190a00572e15423feb7 |
completed | April 19, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69e44fed3fdc81908f4ed6a81db42416 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:44 a.m.