Triple
T28520436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Todd Bowden |
E721746
|
entity |
| Predicate | relationshipToKurtDussander |
P201678
|
FINISHED |
| Object | blackmails him for Holocaust stories |
—
|
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: blackmails him for Holocaust stories | Statement: [Todd Bowden, relationshipToKurtDussander, blackmails him for Holocaust stories]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToKurtDussander Context triple: [Todd Bowden, relationshipToKurtDussander, blackmails him for Holocaust stories]
-
A.
relationshipToDaisyWerthan
Indicates the specific type of personal or social relationship an entity has with Daisy Werthan.
-
B.
relationshipToDudley
Indicates the specific familial or social relationship that one entity has to the person named Dudley.
-
C.
relationshipToTheDude
Indicates the specific type of personal or social relationship that one entity has to the individual referred to as "the Dude."
-
D.
relationshipToTinaBordereau
Indicates the specific type of personal or professional relationship an entity has with Tina Bordereau.
-
E.
relationshipToKenny
Indicates the specific familial, social, or interpersonal connection that one entity has to Kenny.
- 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_69f01a5cbcc4819083fb4e723378713e |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_6a00144238708190acbec3f791cc873e |
completed | May 10, 2026, 5:14 a.m. |
| PD | Predicate disambiguation | batch_6a00120244a4819090ef39070aba9d99 |
completed | May 10, 2026, 5:05 a.m. |
| PDg | Predicate description generation | batch_6a001440a26c81908ba50779bb6e1679 |
completed | May 10, 2026, 5:14 a.m. |
Created at: April 28, 2026, 3:20 a.m.