Triple
T9207217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeff Bingham |
E221012
|
entity |
| Predicate | relationshipTypeWithAdamRhodes |
P10690
|
FINISHED |
| Object | mentor-like |
—
|
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: mentor-like | Statement: [Jeff Bingham, relationshipTypeWithAdamRhodes, mentor-like]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithAdamRhodes Context triple: [Jeff Bingham, relationshipTypeWithAdamRhodes, mentor-like]
-
A.
hasRomanticTensionWith
Indicates a mutual or one-sided romantic attraction or unresolved romantic interest existing between two entities.
-
B.
characterActorRelationship
Indicates a relationship where an actor portrays or is associated with a specific character in a work.
-
C.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more entities.
-
D.
relationshipToJosephCooper
Indicates the specific familial, social, or professional relationship that one entity has to Joseph Cooper.
-
E.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
- F. None of above.
Provenance (3 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_69ca83e9d0e081908bdb71097201a06c |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd9b0b6788190908bee67a0c5d48f |
completed | April 1, 2026, 8:39 a.m. |
| PD | Predicate disambiguation | batch_69cc660af2408190ae06eb8326e1c64e |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:26 p.m.