Triple
T28566682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Missy Cooper |
E722697
|
entity |
| Predicate | relationshipToMaryCooper |
P139462
|
FINISHED |
| Object | daughter |
—
|
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: daughter | Statement: [Missy Cooper, relationshipToMaryCooper, daughter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToMaryCooper Context triple: [Missy Cooper, relationshipToMaryCooper, daughter]
-
A.
relationshipToMary
chosen
Indicates that one entity stands in a specified personal or social relationship to Mary.
-
B.
relationshipToJosephCooper
Indicates the specific familial, social, or professional relationship that one entity has to Joseph Cooper.
-
C.
relationshipToMichelle
Indicates the specific type of relationship or connection that an entity has to Michelle.
-
D.
relationshipToMarcy
Indicates that one entity has a specified personal or social relationship to Marcy.
-
E.
relationshipTypeWithMarnie
Indicates the specific nature or category of relationship that an entity has with Marnie.
- 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_69f01a5f69d08190ad5c0d2167078dec |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_6a002103c93081908398fa5726f5fa6e |
completed | May 10, 2026, 6:09 a.m. |
| PD | Predicate disambiguation | batch_6a001fcb9fb48190a27d8f2ca983fbe6 |
completed | May 10, 2026, 6:03 a.m. |
Created at: April 28, 2026, 4:07 a.m.