Triple
T26828766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rev. Canon Chasuble |
E675438
|
entity |
| Predicate | relationshipToJackWorthing |
P198543
|
FINISHED |
| Object | local clergyman |
—
|
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: local clergyman | Statement: [Rev. Canon Chasuble, relationshipToJackWorthing, local clergyman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToJackWorthing Context triple: [Rev. Canon Chasuble, relationshipToJackWorthing, local clergyman]
-
A.
relationshipToAlgernonMoncrieff
Indicates the specific familial, social, or personal connection that one entity has to Algernon Moncrieff.
-
B.
relationshipToLucyHoneychurch
Indicates the specific type of relationship or connection an entity has to Lucy Honeychurch.
-
C.
relationshipTypeWithGwendolenFairfax
Indicates the specific nature or category of relationship that an entity has with Gwendolen Fairfax.
-
D.
relationshipToNickCharles
Indicates a specified type of personal or social relationship that an entity has with Nick Charles.
-
E.
relationshipTypeWithMargaretSchlegel
Indicates the specific type or nature of the relationship that an entity has with Margaret Schlegel.
- 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_69eee9b776448190993a60b67fcc9545 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69fef2db323c8190821bda53f22a42be |
completed | May 9, 2026, 8:39 a.m. |
| PD | Predicate disambiguation | batch_69fef21d63c88190abf6a99b59b3c655 |
completed | May 9, 2026, 8:36 a.m. |
| PDg | Predicate description generation | batch_69fef2da7d388190a5712a5094741f18 |
completed | May 9, 2026, 8:39 a.m. |
Created at: April 27, 2026, 5 a.m.