Triple
T3143270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dominic |
E65702
|
entity |
| Predicate | loveLifeInfluencedBy |
P9
|
FINISHED |
| Object | Steve Harvey’s relationship advice |
—
|
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: Steve Harvey’s relationship advice | Statement: [Dominic, loveLifeInfluencedBy, Steve Harvey’s relationship advice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: loveLifeInfluencedBy Context triple: [Dominic, loveLifeInfluencedBy, Steve Harvey’s relationship advice]
-
A.
typeOfInfluence
Indicates the specific nature or category of influence that one entity exerts on another.
-
B.
influenced
chosen
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
-
C.
influencesCharacter
Indicates that one entity affects, shapes, or alters the traits, behavior, or development of another entity’s character.
-
D.
placeOfInfluence
Indicates the location or area where an entity exerts significant impact, authority, or cultural, social, or intellectual influence.
-
E.
designInfluenceOn
Indicates that one design, designer, or design-related factor has an effect on shaping, guiding, or altering another design or design outcome.
- 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_69ad8582f564819088c27e1f96153938 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada59489a88190b0962cef091f4ddb |
completed | March 8, 2026, 4:36 p.m. |
| PD | Predicate disambiguation | batch_69ad9dfa3d9081908425aa636bb9b897 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:05 p.m.