Triple
T16813177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benno Levin |
E408666
|
entity |
| Predicate | relationshipToEricPacker |
P124954
|
FINISHED |
| Object | former subordinate |
—
|
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: former subordinate | Statement: [Benno Levin, relationshipToEricPacker, former subordinate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToEricPacker Context triple: [Benno Levin, relationshipToEricPacker, former subordinate]
-
A.
relationshipToTucker
Indicates the specific familial, social, or professional relationship that one entity has to Tucker.
-
B.
relationshipWithTomWambsgans
Indicates the existence and nature of a relationship or connection that an entity has with Tom Wambsgans.
-
C.
relationshipToEdMercer
Indicates the type of personal or professional relationship an entity has with Ed Mercer.
-
D.
relationshipStatusWithDrEvil
Indicates the type or state of a person's relationship with Dr. Evil.
-
E.
relationshipToTinaBordereau
Indicates the specific type of personal or professional relationship an entity has with Tina Bordereau.
- 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_69d88394566c8190b3dcbdc72935f7fa |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b2df5c888190a462614e1432c357 |
completed | April 18, 2026, 4:35 p.m. |
| PD | Predicate disambiguation | batch_69e32b814b188190aee525f8779203cd |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e34fb7c8c8819086975b7955b7d8ef |
completed | April 18, 2026, 9:32 a.m. |
Created at: April 10, 2026, 5:23 a.m.