Triple
T34844451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arrow Electronics |
E1004427
|
entity |
| Predicate | hasNAICSCode |
P45349
|
FINISHED |
| Object | 423690 |
—
|
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: 423690 | Statement: [Arrow Electronics, hasNAICSCode, 423690]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNAICSCode Context triple: [Arrow Electronics, hasNAICSCode, 423690]
-
A.
NAICSCode
chosen
Indicates that an entity is classified under a specific North American Industry Classification System (NAICS) code, defining its primary type of economic activity.
-
B.
SICCode
Indicates the standardized industrial classification code that categorizes the primary type of economic activity associated with an entity or relationship.
-
C.
hasNOCCode
Indicates that an entity is associated with a specific National Occupational Classification (NOC) code that categorizes its occupation or job type.
-
D.
hasIATAIndustryCode
Indicates that an entity is associated with a specific IATA industry code that classifies its role or function in the air transport industry.
-
E.
hasONSCode
Indicates that an entity is associated with a specific code assigned by the Office for National Statistics (ONS) for identification or classification purposes.
- 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_69f76db97714819099b5bed36fd64e9d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff255b84788190a94682f4efe1d0b8 |
completed | May 9, 2026, 12:15 p.m. |
| PD | Predicate disambiguation | batch_69ff24f3ab108190bb017a656cff3d82 |
completed | May 9, 2026, 12:13 p.m. |
Created at: May 3, 2026, 4 p.m.