Triple
T6491740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruth Snyder |
E148053
|
entity |
| Predicate | inceptionOfNotoriety |
P71040
|
FINISHED |
| Object | 1927 |
—
|
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: 1927 | Statement: [Ruth Snyder, inceptionOfNotoriety, 1927]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inceptionOfNotoriety Context triple: [Ruth Snyder, inceptionOfNotoriety, 1927]
-
A.
helpedPropelToMainstreamFame
Indicates that one entity significantly contributed to another entity’s rise to widespread public recognition or mainstream popularity.
-
B.
fameFor
Indicates that one entity is widely known or recognized specifically because of, or in connection with, another entity.
-
C.
wasProminentIn
Indicates that an entity was notably active, influential, or widely recognized within a particular field, context, or time period.
-
D.
notableFor
Indicates that an entity is especially recognized or distinguished for a particular quality, achievement, characteristic, or role.
-
E.
madeProfessionalDebutIn
Indicates the time or event in which an individual first performed or appeared in a professional capacity within a given field or organization.
- 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_69c009088f3081909cd467b05919de30 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a9bf9208190b0957eda06ed3d65 |
completed | March 22, 2026, 10:18 p.m. |
| PD | Predicate disambiguation | batch_69c06740bebc81909d9d6956baa2bcb9 |
completed | March 22, 2026, 10:03 p.m. |
| PDg | Predicate description generation | batch_69c067f1ef148190bc0355abe83f7e16 |
completed | March 22, 2026, 10:06 p.m. |
Created at: March 22, 2026, 4:53 p.m.