Triple
T2812460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen |
E54201
|
entity |
| Predicate | mayBeSpouseOf |
P33561
|
FINISHED |
| Object | Reigning king |
—
|
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: Reigning king | Statement: [Queen, mayBeSpouseOf, Reigning king]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayBeSpouseOf Context triple: [Queen, mayBeSpouseOf, Reigning king]
-
A.
spouseAssociatedWith
chosen
Indicates a marital or spousal relationship or close association between two entities.
-
B.
spouseInstanceOf
Indicates that one entity is the specific spouse (marriage partner) instance of another entity.
-
C.
metSpouseAt
Indicates that one person first encountered or became acquainted with their spouse at a particular place, event, or time.
-
D.
spouseMemberOf
Indicates that a person’s spouse is a member of a specified group, organization, or entity.
-
E.
metSpouseThrough
Indicates that one person became acquainted with and subsequently married their spouse as a result of a particular intermediary person, event, place, or context.
- 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_69ab49de0af08190b3da69683be1e728 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde4a31d081909377044d5ff791b0 |
completed | March 7, 2026, 8:14 a.m. |
| PD | Predicate disambiguation | batch_69abdd0740208190911dc9c9546a79ae |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:59 p.m.