Triple
T16643610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edna Babish |
E404405
|
entity |
| Predicate | relationshipToLaverneDeFazio |
P123695
|
FINISHED |
| Object | stepmother |
—
|
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: stepmother | Statement: [Edna Babish, relationshipToLaverneDeFazio, stepmother]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToLaverneDeFazio Context triple: [Edna Babish, relationshipToLaverneDeFazio, stepmother]
-
A.
relationshipToTinaBordereau
Indicates the specific type of personal or professional relationship an entity has with Tina Bordereau.
-
B.
relationshipToLoretta Castorini
Indicates the specific familial, romantic, or social connection that an entity has to Loretta Castorini.
-
C.
relationshipTypeWithLizzieEustace
Indicates the specific nature or category of relationship that an entity has with Lizzie Eustace.
-
D.
relationshipToLaurie
Indicates the specific type of relationship or connection that an entity has to Laurie.
-
E.
relationshipToLaureyWilliams
Indicates the nature or type of relational connection an entity has specifically to Laurey Williams.
- 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_69d8838a41f08190b0c3f79c47df5078 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37ad3b12c8190a32e33d9ecff9dae |
completed | April 18, 2026, 12:36 p.m. |
| PD | Predicate disambiguation | batch_69e296af2f88819092c9ffee4a65d7dd |
completed | April 17, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69e2d7fb02f481908885a226c2191231 |
completed | April 18, 2026, 1:01 a.m. |
Created at: April 10, 2026, 5:18 a.m.