Triple
T29129747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cathy Simms |
E738338
|
entity |
| Predicate | causesTensionWith |
P61198
|
FINISHED |
| Object | Jim Halpert |
—
|
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: Jim Halpert | Statement: [Cathy Simms, causesTensionWith, Jim Halpert]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causesTensionWith Context triple: [Cathy Simms, causesTensionWith, Jim Halpert]
-
A.
hasRomanticTensionWith
Indicates a mutual or one-sided romantic attraction or unresolved romantic interest existing between two entities.
-
B.
tension
Indicates a state of strain, stress, or conflict existing between entities, often involving opposing forces, interests, or emotions.
-
C.
hasTypeOfTension
Indicates that one entity is associated with, or characterized by, a specific kind or category of tension.
-
D.
hasTension
chosen
Indicates the presence of strain, stress, or conflict between entities in their relationship or interaction.
-
E.
haveRelationshipWith
Indicates that one entity is in some form of defined relationship or association with another entity.
- 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_69f07cb29cdc8190afa55444553de60c |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f7221dc9a88190bb8194fcc29c42bc |
completed | May 3, 2026, 10:23 a.m. |
| PD | Predicate disambiguation | batch_69f72153a9188190b02adc84e1be4af8 |
completed | May 3, 2026, 10:20 a.m. |
Created at: April 28, 2026, 11:30 a.m.