Triple
T5932604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ICH M4 Common Technical Document |
E131971
|
entity |
| Predicate | module1Content |
P2253
|
FINISHED |
| Object | regional administrative information |
—
|
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: regional administrative information | Statement: [ICH M4 Common Technical Document, module1Content, regional administrative information]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: module1Content Context triple: [ICH M4 Common Technical Document, module1Content, regional administrative information]
-
A.
coreModule
Indicates that something functions as a primary or foundational module within a larger system or structure.
-
B.
section3ContentSummary
Indicates a summarized representation of the main points or key information contained in the third section of a document or structure.
-
C.
article1ContentSummary
Indicates a brief, condensed representation of the main points or key information contained in the first article’s content.
-
D.
programContent
Indicates that a program includes or is composed of specific content elements or materials.
-
E.
textOfSection1
chosen
Indicates that the referenced text is the content belonging specifically to section 1 of a larger document or structure.
- 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_69c0085b75e88190a632f9691f9da48b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03f26f51881908cc253fe5775a1fc |
completed | March 22, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_69c03355caf08190b960563a1aed23f9 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 4 p.m.