Triple
T34314303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Theresa of Portugal, Countess of Flanders |
E880534
|
entity |
| Predicate | titleAfterSecondMarriage |
P199398
|
FINISHED |
| Object | Duchess consort of Burgundy |
—
|
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: Duchess consort of Burgundy | Statement: [Theresa of Portugal, Countess of Flanders, titleAfterSecondMarriage, Duchess consort of Burgundy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleAfterSecondMarriage Context triple: [Theresa of Portugal, Countess of Flanders, titleAfterSecondMarriage, Duchess consort of Burgundy]
-
A.
hasFamilyNameAfterSecondMarriage
Indicates that an entity’s family name is the one adopted following their second marriage.
-
B.
spouseTitleOfSecondHusband
Indicates that the object is the formal title or designation held by a person’s second husband.
-
C.
titleAfterDivorce
Indicates the formal title or style a person holds or uses following a divorce.
-
D.
groomTitleAfterMarriage
Indicates that the groom acquires or changes to a specific title following the marriage.
-
E.
laterMarriedName
Indicates that the referenced name is a surname or full name a person adopted after a later marriage, replacing or succeeding their previous name.
- 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_69f349b8bb6c8190ad12a7957a574f04 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff370698ec81909bb1596d7d4112ba |
completed | May 9, 2026, 1:30 p.m. |
| PD | Predicate disambiguation | batch_69ff3699b6288190b564839cb05f5cf6 |
completed | May 9, 2026, 1:28 p.m. |
| PDg | Predicate description generation | batch_69ff3705e424819090ad7423ceefa506 |
completed | May 9, 2026, 1:30 p.m. |
Created at: May 1, 2026, 1:57 a.m.