Triple
T30335843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | murder of Nancy Montgomery |
E771617
|
entity |
| Predicate | sentenceOfGraceMarks |
P168856
|
FINISHED |
| Object | life imprisonment |
—
|
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: life imprisonment | Statement: [murder of Nancy Montgomery, sentenceOfGraceMarks, life imprisonment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sentenceOfGraceMarks Context triple: [murder of Nancy Montgomery, sentenceOfGraceMarks, life imprisonment]
-
A.
marks
Indicates that one entity makes a visible or symbolic sign on, or designates, another entity for identification, emphasis, or distinction.
-
B.
marksOn
Indicates that one entity bears visible signs, traces, or imprints that have been made or left by another entity.
-
C.
sentenceOf
Indicates that one entity is a sentence that belongs to, is contained in, or is part of another larger text or document.
-
D.
marksDetermine
Indicates that one entity’s marks or scores determine or decisively influence the outcome, status, or classification of another entity.
-
E.
recordsDivineStatement
Indicates that one entity documents or preserves a statement, message, or pronouncement made by a divine 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_69f2248aba24819095bb86480d55b23b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f681ccad6c8190b3bf7c0b20c6ffef |
completed | May 2, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69f67603526c81908295a1ece8727c66 |
completed | May 2, 2026, 10:09 p.m. |
| PDg | Predicate description generation | batch_69f676f73c3481909f01fa69851b7298 |
completed | May 2, 2026, 10:13 p.m. |
Created at: April 29, 2026, 7:54 p.m.