Triple
T25189359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amber Waves |
E630820
|
entity |
| Predicate | relationshipTypeWithDirkDiggler |
P179768
|
FINISHED |
| Object | maternal-mentor |
—
|
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: maternal-mentor | Statement: [Amber Waves, relationshipTypeWithDirkDiggler, maternal-mentor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithDirkDiggler Context triple: [Amber Waves, relationshipTypeWithDirkDiggler, maternal-mentor]
-
A.
hasRelationshipTypeWith Frank Drebin
Indicates that there exists a specific type of relationship between an entity and Frank Drebin.
-
B.
relationshipToDudley
Indicates the specific familial or social relationship that one entity has to the person named Dudley.
-
C.
relationshipToTheDude
Indicates the specific type of personal or social relationship that one entity has to the individual referred to as "the Dude."
-
D.
relationshipToBelcherChildren
Indicates the specific familial or caretaking relationship an entity has to the Belcher children.
-
E.
relationshipTypeWithDorothyZbornak
Indicates the specific nature or category of relationship an entity has with Dorothy Zbornak.
- 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_69e75a8a6d088190ba1e82a4345225e7 |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f727afd5d88190ad48735cd1b32787 |
completed | May 3, 2026, 10:47 a.m. |
| PD | Predicate disambiguation | batch_69f72737c42c8190a3f781a5e98868ff |
completed | May 3, 2026, 10:45 a.m. |
| PDg | Predicate description generation | batch_69f727ad9ff88190ba8069dd48b2e98f |
completed | May 3, 2026, 10:47 a.m. |
Created at: April 21, 2026, 12:44 p.m.