Triple
T37863584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miranda Grey |
E944401
|
entity |
| Predicate | relationshipToFrederickClegg |
P204433
|
FINISHED |
| Object | object of obsession |
—
|
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: object of obsession | Statement: [Miranda Grey, relationshipToFrederickClegg, object of obsession]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToFrederickClegg Context triple: [Miranda Grey, relationshipToFrederickClegg, object of obsession]
-
A.
relationshipToFrederic
Indicates the specific type of relationship or connection an entity has to the person named Frederic.
-
B.
relationshipTypeWithCeliaCoplestone
Indicates the specific nature or category of relationship that an entity has with Celia Coplestone.
-
C.
relationshipTypeWithFredGraham
Indicates the specific nature or category of relationship that an entity has with Fred Graham.
-
D.
relationshipToCatherine
Indicates the specific familial, social, or interpersonal connection that one entity has to the person named Catherine.
-
E.
relationshipToFrancis
Indicates the specific familial, social, or professional connection that an entity has with Francis.
- 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_69f76eee2f9c8190b1272aa2ee55ebf5 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037cae084081909004d77514c5f286 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a192a008190a9917688a9e804f4 |
completed | May 12, 2026, 7:06 p.m. |
| PDg | Predicate description generation | batch_6a037c84ecbc81908232e5215355f43b |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:19 p.m.