Triple
T5936527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charter Oath of 1868 |
E132057
|
entity |
| Predicate | hasCanonicalNumberOfArticles |
P67017
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Charter Oath of 1868, hasCanonicalNumberOfArticles, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCanonicalNumberOfArticles Context triple: [Charter Oath of 1868, hasCanonicalNumberOfArticles, 5]
-
A.
hasCanonicalNumber
Indicates that an entity is associated with its officially recognized or standard reference number.
-
B.
hasCanonicalNumberOfHeads
Indicates that an entity possesses the standard or officially recognized number of heads for its kind.
-
C.
hasNumberOfTerms
Indicates the quantity of distinct terms or elements associated with a given entity or expression.
-
D.
hasArticleSystem
Indicates that a language or system employs a structured set of articles (such as definite or indefinite markers) as part of its grammar.
-
E.
hasNumberOfCasesApprox
Indicates that an entity is associated with an approximate (not exact) count of cases.
- 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_69c0085c55dc8190aa90e242c956e2fa |
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. |
| PDg | Predicate description generation | batch_69c03f23dd20819089dbf0de0d913602 |
completed | March 22, 2026, 7:12 p.m. |
Created at: March 22, 2026, 4:01 p.m.