Triple
T265377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Class VI: Technical and Environmental Sciences |
E5710
|
entity |
| Predicate | isSectionNumber |
P8879
|
FINISHED |
| Object | VI |
—
|
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: VI | Statement: [Class VI: Technical and Environmental Sciences, isSectionNumber, VI]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isSectionNumber Context triple: [Class VI: Technical and Environmental Sciences, isSectionNumber, VI]
-
A.
hasSectionCount
Indicates that an entity is associated with a specific number of sections it contains or comprises.
-
B.
section
Indicates that one entity is a distinct part, division, or segment of another entity within a larger whole.
-
C.
numberingType
Indicates the scheme or style used to assign sequential numbers or labels within an ordered set.
-
D.
titleNumber
Indicates the numerical designation or sequence number assigned to a title within an ordered set of titles.
-
E.
containsChapter
Indicates that one entity (typically a larger work or document) includes another entity as a chapter within its structure.
- 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_69a2587daeb081909591b9d30f80a271 |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25d8f9bbc8190a13841e4de093a66 |
completed | Feb. 28, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69a25b6f60b081908fc6467800a8849e |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25c8ae480819094f6d1bb0a6d2eb2 |
completed | Feb. 28, 2026, 3:10 a.m. |
Created at: Feb. 28, 2026, 2:56 a.m.