Triple
T27614802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Cypher of Elizabeth II |
E700411
|
entity |
| Predicate | hasMeaningOfII |
P182218
|
FINISHED |
| Object | the Second |
—
|
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: the Second | Statement: [Royal Cypher of Elizabeth II, hasMeaningOfII, the Second]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMeaningOfII Context triple: [Royal Cypher of Elizabeth II, hasMeaningOfII, the Second]
-
A.
hasMeaningViaJohn
Indicates that something possesses or conveys its meaning specifically through John as the interpretive or mediating agent.
-
B.
hasMultipleMeanings
Indicates that a term, symbol, or expression is associated with more than one distinct meaning or interpretation.
-
C.
hasMean
Indicates that one entity possesses, exhibits, or is characterized by a particular mean value or average.
-
D.
hasMeaningInOriginLanguage
Indicates that something (such as a word, phrase, or symbol) possesses a specific meaning in its original or source language.
-
E.
hasMeaningInJapanese
Indicates that something (such as a word, phrase, or symbol) possesses a specific meaning when interpreted in the Japanese language.
- 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_69ef6a4f1d9c8190b0705acda054368d |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f7886be6d8819095ec62e4f2cee858 |
completed | May 3, 2026, 5:39 p.m. |
| PD | Predicate disambiguation | batch_69f7841440f48190b4346c08855951d2 |
completed | May 3, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69f7886b27f08190ab4580f949222c93 |
completed | May 3, 2026, 5:39 p.m. |
Created at: April 27, 2026, 2:12 p.m.