Triple
T14957863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen Aggravain |
E372978
|
entity |
| Predicate | relationshipToPrincessWinnifred |
P89053
|
FINISHED |
| Object | prospective mother-in-law |
—
|
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: prospective mother-in-law | Statement: [Queen Aggravain, relationshipToPrincessWinnifred, prospective mother-in-law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToPrincessWinnifred Context triple: [Queen Aggravain, relationshipToPrincessWinnifred, prospective mother-in-law]
-
A.
relationshipToPrincess
chosen
Indicates the specific familial, social, or romantic connection that one entity has to a princess.
-
B.
relationshipToQueenOfHearts
Indicates the specific familial, social, or hierarchical relationship that one entity has to the Queen of Hearts.
-
C.
princessOf
Indicates that one entity holds the royal title or role of princess in relation to another entity, typically a realm, family, or sovereign.
-
D.
relationshipToEarlJr
Indicates the specific familial or social relationship that an entity has to Earl Jr.
-
E.
relationshipToJohanna
Indicates the specific type of relationship or connection that an entity has with Johanna.
- 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_69d85cca979481908747d2a81eba1cea |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6cd85bc81909040b7ff78f62554 |
completed | April 15, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69de9a5d995881909e33658f5aea5582 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:40 a.m.