Triple
T33458806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seduction by Mrs. Robinson |
E856850
|
entity |
| Predicate | counterpartPortrayedBy |
P202779
|
FINISHED |
| Object | Dustin Hoffman |
—
|
NE NERFINISHED |
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: Dustin Hoffman | Statement: [Seduction by Mrs. Robinson, counterpartPortrayedBy, Dustin Hoffman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: counterpartPortrayedBy Context triple: [Seduction by Mrs. Robinson, counterpartPortrayedBy, Dustin Hoffman]
-
A.
counterpartRelation
Indicates a reciprocal relationship where two entities serve as corresponding or equivalent counterparts to each other in a given context.
-
B.
counterpartTerm
Indicates that one term serves as a corresponding or equivalent term to another within a specific relational or comparative context.
-
C.
counterpartVersion
Indicates a version relationship where one entity serves as the corresponding or matching version of another entity in a different context, system, or side of an interaction.
-
D.
hasCounterpart
Indicates that one entity corresponds to, matches, or serves as an equivalent or parallel version of another entity.
-
E.
counterpartService
Indicates that one service functions as the corresponding or matching service to another within a defined relationship or context.
- 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_69f3497281a08190b4705de0b5f26ba7 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a00b7fb90f881908f73edf2be8cc3a5 |
completed | May 10, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_6a00b75593d08190b3e76191cd79cdec |
completed | May 10, 2026, 4:50 p.m. |
| PDg | Predicate description generation | batch_6a00b7faee908190906aae5233ea3122 |
completed | May 10, 2026, 4:53 p.m. |
Created at: May 1, 2026, 1:37 a.m.