Triple
T19360636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sibylla of Conversano |
E484268
|
entity |
| Predicate | spouseOrderInFamily |
P4764
|
FINISHED |
| Object | eldest son of William the Conqueror |
—
|
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: eldest son of William the Conqueror | Statement: [Sibylla of Conversano, spouseOrderInFamily, eldest son of William the Conqueror]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseOrderInFamily Context triple: [Sibylla of Conversano, spouseOrderInFamily, eldest son of William the Conqueror]
-
A.
spouseOrder
chosen
Indicates the position or sequence of a person among multiple spouses in a marital relationship.
-
B.
spouseInFamily
Indicates that a person is a spouse (married partner) within the context of a specific family unit.
-
C.
hasSpousePositionInFamily
Indicates that a person’s spouse holds a specific role or position within the family structure.
-
D.
spouseFamily
Indicates a family relationship formed through marriage, such as between a person and their spouse’s relatives.
-
E.
spouseType
Indicates the specific role or category of a person within a spousal relationship (e.g., husband, wife, partner).
- 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_69d8e8d305088190ad13571532aa454c |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e6190c2a8081908f48dfa738248ec8 |
completed | April 20, 2026, 12:16 p.m. |
| PD | Predicate disambiguation | batch_69e4dd13a8cc81909cd02668564c9f29 |
completed | April 19, 2026, 1:48 p.m. |
Created at: April 10, 2026, 1:34 p.m.