Triple
T33462584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Patrick Augustus Duncan |
E856959
|
entity |
| Predicate | impactOnOther |
P103390
|
FINISHED |
| Object | deeply affected Isadora Duncan's life |
—
|
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: deeply affected Isadora Duncan's life | Statement: [Patrick Augustus Duncan, impactOnOther, deeply affected Isadora Duncan's life]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnOther Context triple: [Patrick Augustus Duncan, impactOnOther, deeply affected Isadora Duncan's life]
-
A.
impactStatus
Indicates the current state or condition of how something has affected or influenced a target.
-
B.
impactDescription
chosen
Indicates a description of the effect, consequence, or influence that one entity, action, or event has on another.
-
C.
effectOnOthers
Indicates the impact or influence that one entity’s actions, presence, or state has on other entities.
-
D.
impactOnSubject
Indicates the effect, influence, or consequence that one entity, event, or action has on a specified subject.
-
E.
exportImpact
Indicates the effect or consequences that an entity’s exports have on another entity, system, or context.
- 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_69f34973461481909c701c98ebd75623 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7b0e5744c8190a22c1e1d6fcfa466 |
completed | May 3, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f7ab70d034819080295628497d8582 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 1, 2026, 1:37 a.m.