Triple
T33327486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mayordomo mayor de la Casa Real |
E853303
|
entity |
| Predicate | tieneTítuloEnOtrasLenguas |
P15390
|
FINISHED |
| Object | Grand Majordome de la Maison Royale |
—
|
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: Grand Majordome de la Maison Royale | Statement: [Mayordomo mayor de la Casa Real, tieneTítuloEnOtrasLenguas, Grand Majordome de la Maison Royale]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tieneTítuloEnOtrasLenguas Context triple: [Mayordomo mayor de la Casa Real, tieneTítuloEnOtrasLenguas, Grand Majordome de la Maison Royale]
-
A.
titleInLanguage
Indicates that a specific title or name is expressed in a particular language.
-
B.
hasTitleInLanguage
chosen
Indicates that an entity has a specific title expressed in a particular language.
-
C.
hasLatinTitleOf
Indicates that one entity has, uses, or is associated with the Latin-language title corresponding to another entity.
-
D.
titleInLocalLanguage
Indicates that an entity’s title is expressed in the primary or native language of a specified place or community.
-
E.
hasTitleInOriginalWork
Indicates that an entity holds a specific title or designation within its original work or source context.
- 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_69f349685f088190b8fda44083a018a9 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6e3156ea48190b604e414665ef351 |
completed | May 3, 2026, 5:54 a.m. |
| PD | Predicate disambiguation | batch_69f6de0b9ba48190887c9eb5d06a2e94 |
completed | May 3, 2026, 5:32 a.m. |
Created at: May 1, 2026, 1:33 a.m.