Triple
T11872708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Life-Model Decoys |
E282441
|
entity |
| Predicate | commonPlotUse |
P101982
|
FINISHED |
| Object | allow leaders to survive assassination attempts |
—
|
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: allow leaders to survive assassination attempts | Statement: [Life-Model Decoys, commonPlotUse, allow leaders to survive assassination attempts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonPlotUse Context triple: [Life-Model Decoys, commonPlotUse, allow leaders to survive assassination attempts]
-
A.
commonFor
Indicates that something is typical, usual, or frequently occurring for a given entity or context.
-
B.
commonIn
Indicates that something frequently occurs, appears, or is found within a specified context, group, or environment.
-
C.
widelyUsedIn
Indicates that something is commonly or extensively utilized within a particular context, domain, or group.
-
D.
usageAmong
Indicates how frequently or in what manner something is used within a particular group, context, or population.
-
E.
usedAcross
Indicates that something is utilized or applied in multiple different contexts, locations, or domains.
- 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8d39d2934819093b9f7006f45e5cb |
completed | April 10, 2026, 10:40 a.m. |
| PD | Predicate disambiguation | batch_69d8bb272f88819090c37c944c5a60ab |
completed | April 10, 2026, 8:56 a.m. |
| PDg | Predicate description generation | batch_69d8d399d58c81908dab572aa82426d7 |
completed | April 10, 2026, 10:40 a.m. |
Created at: April 8, 2026, 9:43 p.m.