Triple
T33090178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ellen |
E846758
|
entity |
| Predicate | hasRelationshipToGladysGreen |
P204179
|
FINISHED |
| Object | granddaughter |
—
|
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: granddaughter | Statement: [Ellen, hasRelationshipToGladysGreen, granddaughter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelationshipToGladysGreen Context triple: [Ellen, hasRelationshipToGladysGreen, granddaughter]
-
A.
relationshipToSheilaGreene
Indicates the specific type of relationship or connection an entity has to Sheila Greene.
-
B.
hasRelationshipToJackTorrance
Indicates that one entity has some form of relationship or connection to Jack Torrance.
-
C.
relationshipTypeWithGlendaParks
Indicates the specific nature or category of relationship that an entity has with Glenda Parks.
-
D.
relationshipToGeorgeAndMartha
Indicates the specific familial, social, or other relational connection that an entity has to the pair George and Martha considered together.
-
E.
hasRelationshipTypeWith Frank Drebin
Indicates that there exists a specific type of relationship between an entity and Frank Drebin.
- 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_69f3495590dc8190aa04f3dec74ce976 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a03446ec72881909c5ff25a48baadb3 |
completed | May 12, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_6a03439b393c819084aa9b7ed0d5b6b0 |
completed | May 12, 2026, 3:13 p.m. |
| PDg | Predicate description generation | batch_6a03446d9d988190981f245d74c3444b |
completed | May 12, 2026, 3:17 p.m. |
Created at: May 1, 2026, 1:26 a.m.