Triple
T31339176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | His Majesty the King of Italy |
E799257
|
entity |
| Predicate | correspondsToTitleInItalian |
P48373
|
FINISHED |
| Object | Re d'Italia |
—
|
NE NERFINISHED |
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: Re d'Italia | Statement: [His Majesty the King of Italy, correspondsToTitleInItalian, Re d'Italia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: correspondsToTitleInItalian Context triple: [His Majesty the King of Italy, correspondsToTitleInItalian, Re d'Italia]
-
A.
equivalentTitleInItalian
chosen
Indicates that one entity’s title is an equivalent version of another entity’s title expressed in Italian.
-
B.
titleInItalian
Indicates that one entity is the title of another entity expressed in the Italian language.
-
C.
correspondsToAbbreviationInItalian
Indicates that one entity is the full form or concept for which the other entity serves as an abbreviation in Italian.
-
D.
correspondsToItalianAbbreviation
Indicates that one entity is the Italian-language abbreviation or acronym that corresponds to, or represents, the other entity.
-
E.
hasLatinTitleOf
Indicates that one entity has, uses, or is associated with the Latin-language title corresponding to another entity.
- 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_69f224e3f6ac8190a13488516abca7c9 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f7221dc9a88190bb8194fcc29c42bc |
completed | May 3, 2026, 10:23 a.m. |
| PD | Predicate disambiguation | batch_69f72153a9188190b02adc84e1be4af8 |
completed | May 3, 2026, 10:20 a.m. |
Created at: April 29, 2026, 9:16 p.m.