Triple
T29541930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LGM-118A Peacekeeper |
E749523
|
entity |
| Predicate | accuracyCategory |
P159023
|
FINISHED |
| Object | high-accuracy ICBM |
—
|
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: high-accuracy ICBM | Statement: [LGM-118A Peacekeeper, accuracyCategory, high-accuracy ICBM]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: accuracyCategory Context triple: [LGM-118A Peacekeeper, accuracyCategory, high-accuracy ICBM]
-
A.
curacy
Indicates that one entity serves in the role or position of a curate (assistant clergy) in relation to another entity, typically a parish or church.
-
B.
hasAccuracy
Indicates that something possesses a specified level or measure of correctness, precision, or exactness in relation to a standard or reference.
-
C.
accuracyDependsOn
Indicates that the accuracy of one entity or process is contingent upon, or influenced by, another entity or factor.
-
D.
accuracyCharacterization
chosen
Indicates how precisely or reliably something is described, measured, or represented in relation to a given standard or truth.
-
E.
rankingCategory
Indicates the classification or type of ranking under which an entity is evaluated or ordered.
- 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_69f0bd48691081908cecad39bac591e0 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f66ccb2f0c8190afec245ff546681c |
completed | May 2, 2026, 9:29 p.m. |
| PD | Predicate disambiguation | batch_69f6633ac8a88190ab0cda62bbfcf9b0 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 28, 2026, 5:03 p.m.