Triple
T30841612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrs. Sappleton |
E785525
|
entity |
| Predicate | relationToVera |
P94755
|
FINISHED |
| Object | aunt |
—
|
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: aunt | Statement: [Mrs. Sappleton, relationToVera, aunt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationToVera Context triple: [Mrs. Sappleton, relationToVera, aunt]
-
A.
relationToVonMaur
Indicates a specified type of relationship or association that an entity has with Von Maur.
-
B.
relationshipToRelative
chosen
Indicates the specific familial connection or kinship role that one person has in relation to a particular relative.
-
C.
relationToBabo
Indicates a relationship or connection that an entity has to the person or entity referred to as "Babo."
-
D.
relationToPenelope
Indicates a relational connection that one entity has specifically toward Penelope.
-
E.
relationshipToVeronika
Indicates the specific type of personal, social, or familial relationship that one entity has to Veronika.
- 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_69f224b850848190a4af4ccf8ddadcdf |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a036b0755888190a68a673664f0ea46 |
completed | May 12, 2026, 6:01 p.m. |
| PD | Predicate disambiguation | batch_6a036228676c8190aac9c90f7d8cedf7 |
completed | May 12, 2026, 5:23 p.m. |
Created at: April 29, 2026, 8:45 p.m.