Triple
T35854488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jimmy Barrett |
E1036458
|
entity |
| Predicate | causesTensionFor |
P174943
|
FINISHED |
| Object | Betty Draper |
—
|
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: Betty Draper | Statement: [Jimmy Barrett, causesTensionFor, Betty Draper]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causesTensionFor Context triple: [Jimmy Barrett, causesTensionFor, Betty Draper]
-
A.
tension
Indicates a state of strain, stress, or conflict existing between entities, often involving opposing forces, interests, or emotions.
-
B.
hasTypeOfTension
Indicates that one entity is associated with, or characterized by, a specific kind or category of tension.
-
C.
hasTension
Indicates the presence of strain, stress, or conflict between entities in their relationship or interaction.
-
D.
tensionSource
chosen
Indicates that one entity is the origin or cause of tension affecting another entity or situation.
-
E.
tensionMethod
Indicates the method or technique used to apply or maintain tension in a system or between components.
- 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_69f76e1b4aa481909630373171eb5ec6 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fd4129a8848190a5002150278ac689 |
completed | May 8, 2026, 1:49 a.m. |
| PD | Predicate disambiguation | batch_69fd3e0515ec8190937c7af71ebc3875 |
completed | May 8, 2026, 1:36 a.m. |
Created at: May 3, 2026, 4:06 p.m.