Triple
T9819729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henrietta Maria |
E238497
|
entity |
| Predicate | hasEponymTitle |
P56375
|
FINISHED |
| Object | Queen of England |
—
|
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: Queen of England | Statement: [Henrietta Maria, hasEponymTitle, Queen of England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEponymTitle Context triple: [Henrietta Maria, hasEponymTitle, Queen of England]
-
A.
hasTitleNamesake
Indicates that one entity serves as the namesake or source of the title borne by another entity.
-
B.
hasEponymConnectionTo
chosen
Indicates that one entity is named after, derived from, or otherwise linguistically or honorifically connected to another entity as its eponym.
-
C.
isNamedForEponymRole
Indicates that one entity bears a name derived from another entity that serves as its eponym or namesake.
-
D.
eraTitleWith
Indicates a relationship where a specific era is associated with or designated by a particular title.
-
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_69ca84dfde1481909f47c286d715f892 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb2f74e348190be8e4394ae6fe3fe |
completed | April 2, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69cd03e01ea881909a7d93fc3994ace5 |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:31 p.m.