Triple
T31112779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frances |
E792996
|
entity |
| Predicate | codeNameAppliesTo |
P82190
|
FINISHED |
| Object | Yokosuka P1Y series |
—
|
NE NERFINISHED |
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: Yokosuka P1Y series | Statement: [Frances, codeNameAppliesTo, Yokosuka P1Y series]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: codeNameAppliesTo Context triple: [Frances, codeNameAppliesTo, Yokosuka P1Y series]
-
A.
nameAppliesTo
chosen
Indicates that a particular name is assigned to, or valid for use with, a specific entity.
-
B.
appliesTo
Indicates that something is relevant, valid, or has effect in relation to a particular entity, case, or context.
-
C.
appliesAlsoTo
Indicates that a condition, rule, or characteristic that applies to one entity is additionally applicable to another entity.
-
D.
appliesAt
Indicates that an action, rule, or condition is relevant to or in effect at a specific location, context, or point in time.
-
E.
appliesVia
Indicates that an action, rule, or effect is carried out, implemented, or achieved through a specified method, medium, or mechanism.
- 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_69f224cfd5d881908ec6447bc321cd58 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69c234d648190a243fb2b107136a9 |
completed | May 3, 2026, 12:51 a.m. |
| PD | Predicate disambiguation | batch_69f69665cd9c819088c388fc82fec42e |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 29, 2026, 9:04 p.m.