Triple
T264466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PK |
E5694
|
entity |
| Predicate | relatedStandardCode |
P5026
|
FINISHED |
| Object | PAK |
—
|
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: PAK | Statement: [PK, relatedStandardCode, PAK]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedStandardCode Context triple: [PK, relatedStandardCode, PAK]
-
A.
relatedCode
chosen
Indicates that one code is associated with, linked to, or otherwise contextually connected to another code.
-
B.
relatedTo
Indicates a general, non-specific relationship or association exists between two entities.
-
C.
legalStandardHistoricallyAssociatedWith
Indicates that a particular legal standard has been historically linked or traditionally associated with another legal concept, practice, or context.
-
D.
relatedField
Indicates that one field, topic, or area of study is connected or relevant to another in subject matter or application.
-
E.
standardizedBy
Indicates that one entity defines, regulates, or formalizes the standards or specifications by which another entity is created, measured, or operated.
- 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_69a2587daeb081909591b9d30f80a271 |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25d8e809881908a58c9a4e3ba07c3 |
completed | Feb. 28, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69a25b6e07748190834022a65ba6d803 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:56 a.m.