Triple
T29184362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miss Mary Shepherd |
E739824
|
entity |
| Predicate | relationshipToAlanBennett |
P203012
|
FINISHED |
| Object | neighbor |
—
|
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: neighbor | Statement: [Miss Mary Shepherd, relationshipToAlanBennett, neighbor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToAlanBennett Context triple: [Miss Mary Shepherd, relationshipToAlanBennett, neighbor]
-
A.
relationshipWithAlanHarper
Indicates that one entity has a specified type of personal or social relationship with Alan Harper.
-
B.
relationshipToSamuelBeckett
Indicates the specific type of personal, professional, or familial relationship that one entity has to Samuel Beckett.
-
C.
relationshipWithJohnBennett
Indicates that there exists some specified type of relationship or association between an entity and John Bennett.
-
D.
relationshipToKittyBennet
Indicates the specific type of personal or familial connection an entity has to Kitty Bennet.
-
E.
relationshipToAlbertNobbs
Indicates that one entity has a specified personal, social, or narrative connection to the person or character named Albert Nobbs.
- 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_69f07cb74c2c8190ad396487fcb4fde6 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_6a00dc330b148190aaae2ac6a5327960 |
completed | May 10, 2026, 7:27 p.m. |
| PD | Predicate disambiguation | batch_6a00d9d2904881909dafbfe7b9e5ad81 |
completed | May 10, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_6a00dc3268248190a723e1b7b29f9cda |
completed | May 10, 2026, 7:27 p.m. |
Created at: April 28, 2026, 11:59 a.m.