Triple
T28950754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ygerna |
E731006
|
entity |
| Predicate | spouseSequence |
P178587
|
FINISHED |
| Object | first Gorlois then Uther Pendragon |
—
|
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: first Gorlois then Uther Pendragon | Statement: [Ygerna, spouseSequence, first Gorlois then Uther Pendragon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseSequence Context triple: [Ygerna, spouseSequence, first Gorlois then Uther Pendragon]
-
A.
spouseOfSequence
chosen
Indicates a sequential or ordered relationship of being spouses, where each entity is married to the next in the sequence.
-
B.
spouseOrder
Indicates the position or sequence of a person among multiple spouses in a marital relationship.
-
C.
motherSpouseOrder
Indicates that the subject is the spouse of the object’s mother, with an ordering or ranking among multiple such spouses.
-
D.
spouseOfType
Indicates that one entity is the spouse of another, specifying the type or role of that spousal relationship.
-
E.
spouseOfChildren
Indicates that one entity is the spouse (husband or wife) of the children 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_69f043eb9bcc819091ac7b07aecb6475 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f74c70fd248190a9d5543afcb08211 |
completed | May 3, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69f7478e3b548190a51d5d436e2bb036 |
completed | May 3, 2026, 1:03 p.m. |
Created at: April 28, 2026, 8:43 a.m.