Triple
T26828626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cecily Cardew |
E675435
|
entity |
| Predicate | relationshipTypeWithGwendolenFairfax |
P198433
|
FINISHED |
| Object | rival then friend |
—
|
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: rival then friend | Statement: [Cecily Cardew, relationshipTypeWithGwendolenFairfax, rival then friend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithGwendolenFairfax Context triple: [Cecily Cardew, relationshipTypeWithGwendolenFairfax, rival then friend]
-
A.
relationshipTypeWithBertieWooster
Indicates the specific nature or category of relationship an entity has with Bertie Wooster.
-
B.
relationshipTypeWithMargaretSchlegel
Indicates the specific type or nature of the relationship that an entity has with Margaret Schlegel.
-
C.
relationshipToNickCharles
Indicates a specified type of personal or social relationship that an entity has with Nick Charles.
-
D.
relationshipToBertieWooster
Indicates the specific type of personal or social relationship an entity has with Bertie Wooster.
-
E.
relationshipToEmmaWoodhouse
Indicates the specific interpersonal or familial connection that an entity has to Emma Woodhouse.
- 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_69fee335cb08819097e3a0e09d5ebf49 |
completed | May 9, 2026, 7:33 a.m. |
| PD | Predicate disambiguation | batch_69fee2c74fd88190acfc045ab07b7f6b |
completed | May 9, 2026, 7:31 a.m. |
| PDg | Predicate description generation | batch_69fee33485188190a43526c9d39e3b6a |
completed | May 9, 2026, 7:33 a.m. |
Created at: April 27, 2026, 5 a.m.