Triple
T34306303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lionel Croy |
E880315
|
entity |
| Predicate | impactOnKateCroy |
P103390
|
FINISHED |
| Object | contributes to Kate Croy's precarious social position |
—
|
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: contributes to Kate Croy's precarious social position | Statement: [Lionel Croy, impactOnKateCroy, contributes to Kate Croy's precarious social position]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnKateCroy Context triple: [Lionel Croy, impactOnKateCroy, contributes to Kate Croy's precarious social position]
-
A.
impactOnDirector
Indicates that one entity has an effect, influence, or consequence on a director in the context of a given situation or action.
-
B.
impactDescription
chosen
Indicates a description of the effect, consequence, or influence that one entity, action, or event has on another.
-
C.
impactOnFamily
Indicates the effect or influence that something has on a family’s situation, dynamics, or well-being.
-
D.
impactStatus
Indicates the current state or condition of how something has affected or influenced a target.
-
E.
impactCategory
Indicates the type or domain of effect that one entity or action has on another, classifying the nature of its impact.
- 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_69f349b8bb6c8190ad12a7957a574f04 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7bbf906d8819099020e548dd56bc9 |
completed | May 3, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a2dcf88190a7c9e109e41267be |
completed | May 3, 2026, 9:09 p.m. |
Created at: May 1, 2026, 1:57 a.m.