Triple
T27206937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinese women’s distance running squad |
E683889
|
entity |
| Predicate | impactOnRecords |
P103390
|
FINISHED |
| Object | dramatic lowering of women’s distance world records in early 1990s |
—
|
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: dramatic lowering of women’s distance world records in early 1990s | Statement: [Chinese women’s distance running squad, impactOnRecords, dramatic lowering of women’s distance world records in early 1990s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnRecords Context triple: [Chinese women’s distance running squad, impactOnRecords, dramatic lowering of women’s distance world records in early 1990s]
-
A.
affectedRecord
Indicates that one entity is a record that is impacted, modified, or otherwise influenced as a result of an action or event involving another entity.
-
B.
impactStatus
Indicates the current state or condition of how something has affected or influenced a target.
-
C.
migrationImpact
Indicates how migration influences or changes conditions, outcomes, or states within a given context.
-
D.
impactDescription
chosen
Indicates a description of the effect, consequence, or influence that one entity, action, or event has on another.
-
E.
encodingImpact
Indicates how one encoding or encoding choice affects, modifies, or constrains another process, representation, or 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_69eefad339a08190aeacb2a198f1a39b |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f69383222c81909d8baa04129d5c81 |
completed | May 3, 2026, 12:14 a.m. |
| PD | Predicate disambiguation | batch_69f690eb1e948190aab41a89969519a5 |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 27, 2026, 9:38 a.m.