Triple
T12884464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrs Poyser |
E308189
|
entity |
| Predicate | relationshipToHettySorrel |
P107439
|
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 Poyser, relationshipToHettySorrel, aunt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToHettySorrel Context triple: [Mrs Poyser, relationshipToHettySorrel, aunt]
-
A.
relationshipToHesterPrynne
Indicates the specific familial, social, or emotional connection that an entity has to Hester Prynne.
-
B.
relationshipToPatsey
Indicates the nature or type of relationship an entity has with the person or entity named Patsey.
-
C.
relationshipToLordEmsworth
Indicates the specific social or familial relationship that an entity has to Lord Emsworth.
-
D.
relationshipToCatherine
Indicates the specific familial, social, or interpersonal connection that one entity has to the person named Catherine.
-
E.
relationshipToIsabelArcher
Indicates the specific personal or social connection that an entity has to Isabel Archer.
- 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_69d7bdf7c1f0819098102569a8d8cbf5 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97c7f91d08190aac2f6419d3ba992 |
completed | April 10, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69d96fa55b888190ab1612e93c41aec4 |
completed | April 10, 2026, 9:46 p.m. |
| PDg | Predicate description generation | batch_69d97c7d0598819080cab0a2314bc106 |
completed | April 10, 2026, 10:41 p.m. |
Created at: April 9, 2026, 5:39 p.m.