Triple
T34056613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matt Mickiewicz |
E873374
|
entity |
| Predicate | languageOfBusinessContent |
P148525
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Matt Mickiewicz, languageOfBusinessContent, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfBusinessContent Context triple: [Matt Mickiewicz, languageOfBusinessContent, English]
-
A.
contentLanguage
Indicates the language in which the content is expressed or intended to be understood.
-
B.
لغة_الأعمال
chosen
Indicates a relationship where something is expressed, conducted, or communicated using the language of business (لغة الأعمال).
-
C.
languageOfCommunications
Indicates that a specified language is used as the medium for communications associated with an entity or interaction.
-
D.
languageOfCustom
Indicates that a particular language is used to express, perform, or transmit a given custom or cultural practice.
-
E.
languageOfProduct
Indicates the language in which a product is written, labeled, presented, or otherwise made available.
- 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_69f349a3ec2c8190b62da76e54231a0f |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a004b6ad4248190b402a0d01b0ebf83 |
completed | May 10, 2026, 9:10 a.m. |
| PD | Predicate disambiguation | batch_6a004ae736b881908a0efed8f63f982e |
completed | May 10, 2026, 9:07 a.m. |
Created at: May 1, 2026, 1:52 a.m.