Triple
T26249372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Woodhouse |
E656537
|
entity |
| Predicate | relationshipToEmmaWoodhouse |
P196035
|
FINISHED |
| Object | father |
—
|
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: father | Statement: [Mr. Woodhouse, relationshipToEmmaWoodhouse, father]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToEmmaWoodhouse Context triple: [Mr. Woodhouse, relationshipToEmmaWoodhouse, father]
-
A.
relationshipToElinorDashwood
Indicates the specific familial, social, or interpersonal connection that one entity has to Elinor Dashwood.
-
B.
relationshipToMarianneDashwood
Indicates the specific familial, social, or emotional connection that an entity has to Marianne Dashwood.
-
C.
relationshipToJaneBennet
Indicates the specific familial, social, or emotional connection that one entity has to Jane Bennet.
-
D.
relationshipToLordEmsworth
Indicates the specific social or familial relationship that an entity has to Lord Emsworth.
-
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_69ee5b4d25ac819086acb51184602576 |
completed | April 26, 2026, 6:37 p.m. |
| NER | Named-entity recognition | batch_69fe031bc6208190860099aef72d8dcb |
completed | May 8, 2026, 3:36 p.m. |
| PD | Predicate disambiguation | batch_69fe014c8b388190b5d4e0cb95ee2be5 |
completed | May 8, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69fe031af3248190816da6829aef7bab |
completed | May 8, 2026, 3:36 p.m. |
Created at: April 26, 2026, 9:06 p.m.