Triple
T34895061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George |
E1006406
|
entity |
| Predicate | relationshipToNickAdams |
P205597
|
FINISHED |
| Object | adult guide figure |
—
|
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: adult guide figure | Statement: [George, relationshipToNickAdams, adult guide figure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToNickAdams Context triple: [George, relationshipToNickAdams, adult guide figure]
-
A.
relationshipToNina
Indicates that one entity has a specified personal or social relationship to Nina.
-
B.
relationshipToNicholas
Indicates the specific familial, social, or professional relationship that one entity has to Nicholas.
-
C.
relationshipToJoadFamily
Indicates the specific familial or social connection an entity has with members of the Joad family.
-
D.
relationshipToNickSalter
Indicates the specific type of personal or professional relationship an entity has with Nick Salter.
-
E.
relationshipToPete
Indicates the specific type of relationship or connection that an entity has to Pete.
- 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_69f76dbfe5788190ad8b64f241f470c8 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379ff1ba081908eda86acefcf69fb |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4 p.m.