Triple
T448046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indian Independence Act 1947 |
E7063
|
entity |
| Predicate | chapterNumber |
P14913
|
FINISHED |
| Object | 30 & 31 Geo 6 c. 30 |
—
|
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: 30 & 31 Geo 6 c. 30 | Statement: [Indian Independence Act 1947, chapterNumber, 30 & 31 Geo 6 c. 30]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chapterNumber Context triple: [Indian Independence Act 1947, chapterNumber, 30 & 31 Geo 6 c. 30]
-
A.
numberOfChapters
Indicates the total count of chapters associated with a given entity.
-
B.
containsChapter
Indicates that one entity (typically a larger work or document) includes another entity as a chapter within its structure.
-
C.
chapterNumberInLuke
Indicates the chapter number that a referenced passage or event appears in within the Book of Luke.
-
D.
shortestChapter
Indicates that one chapter is the shortest in length (e.g., by word count or pages) among a set of chapters.
-
E.
editionNumber
Indicates the specific sequential number assigned to an edition of a work within its series of published versions.
- 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_69a2e7e4676c81909ea0dbdecac0687c |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ef6429e881908aa758da64299a16 |
completed | Feb. 28, 2026, 1:36 p.m. |
| PD | Predicate disambiguation | batch_69a2ede1a1108190a4a06b3416ae6156 |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2ef611b9c8190ac5e9174744d9127 |
completed | Feb. 28, 2026, 1:36 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.