Triple
T29447814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wulfhall |
E746896
|
entity |
| Predicate | linkedToConsort |
P188088
|
FINISHED |
| Object | Jane Seymour |
—
|
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: Jane Seymour | Statement: [Wulfhall, linkedToConsort, Jane Seymour]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linkedToConsort Context triple: [Wulfhall, linkedToConsort, Jane Seymour]
-
A.
associatedConsort
Indicates a spousal or consort relationship linking one entity to another as their partner.
-
B.
holderConsort
Indicates a marital or consort relationship in which one entity is the spouse or consort of the title- or office-holding entity.
-
C.
providedConsortTo
Indicates that one entity served as the consort (spouse or partner) to another entity.
-
D.
notableConsort
Indicates that one entity is a spouse or consort of another who is notable or significant in some recognized context.
-
E.
possibleConsortOf
Indicates that one entity is a potential or likely romantic or marital partner of another, without asserting that the relationship is confirmed.
- 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_69f0a7a230488190b44a97fe3d16f731 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69fba2877b248190a974eb092243c0c4 |
completed | May 6, 2026, 8:20 p.m. |
| PD | Predicate disambiguation | batch_69fb8d06a1b48190a937aa410d159dfa |
completed | May 6, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69fba28684208190921694f23e350c3b |
completed | May 6, 2026, 8:20 p.m. |
Created at: April 28, 2026, 3:29 p.m.