Triple
T37316649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ana de Quesada y Loynaz |
E926353
|
entity |
| Predicate | spouseHonorificTitleOfHusband |
P17687
|
FINISHED |
| Object | Father of the Cuban Nation |
—
|
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: Father of the Cuban Nation | Statement: [Ana de Quesada y Loynaz, spouseHonorificTitleOfHusband, Father of the Cuban Nation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseHonorificTitleOfHusband Context triple: [Ana de Quesada y Loynaz, spouseHonorificTitleOfHusband, Father of the Cuban Nation]
-
A.
spouseNameWithTitle
Indicates that a person’s spouse is identified by name together with an associated honorific or title.
-
B.
honorificPrefixOfSpouse
Indicates that a specified honorific prefix (e.g., Mr., Dr., Lady) is used as the formal title for a person’s spouse.
-
C.
hasSpouseTitle
chosen
Indicates that a person’s spouse holds a particular title or honorific designation.
-
D.
spouseTitleOfSecondHusband
Indicates that the object is the formal title or designation held by a person’s second husband.
-
E.
isSpouseOfTitle
Indicates that one entity holds a spousal relationship specifically associated with a titled or honorific status of 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_69f76eb28af88190b093b32e3fd614ab |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69feb5e66224819083b87c3707a5a5e0 |
completed | May 9, 2026, 4:19 a.m. |
| PD | Predicate disambiguation | batch_69feb3bd700c8190991ed200cd3c04db |
completed | May 9, 2026, 4:10 a.m. |
Created at: May 3, 2026, 4:16 p.m.