Triple
T35906938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jane Pierce |
E1038497
|
entity |
| Predicate | impactOfTragedy |
P188478
|
FINISHED |
| Object | withdrew further from public 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: withdrew further from public life | Statement: [Jane Pierce, impactOfTragedy, withdrew further from public life]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOfTragedy Context triple: [Jane Pierce, impactOfTragedy, withdrew further from public life]
-
A.
otherMajorTragedy
Indicates that the subject experienced or was involved in a significant tragic event other than the primary or most notable tragedy under consideration.
-
B.
impactOfDisasters
Indicates the effects or consequences that disasters have on entities, conditions, or outcomes.
-
C.
casualtiesImpact
Indicates how the number or severity of casualties affects or influences another factor, situation, or outcome.
-
D.
narrativeImpactOn
Indicates how one element influences, shapes, or alters the narrative significance or storyline of another.
-
E.
impactOnFamily
Indicates the effect or influence that something has on a family’s situation, dynamics, or well-being.
- F. None of above. chosen
Provenance (4 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_69f76e2259608190bf6788a132e0d139 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fba78aca4c8190b8f1831e8cc04e06 |
completed | May 6, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69fba34a65a4819088bac6c17542d71c |
completed | May 6, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69fba789c1188190973a919bfe2871f3 |
completed | May 6, 2026, 8:41 p.m. |
Created at: May 3, 2026, 4:07 p.m.