Triple
T32415695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Azure workloads |
E828325
|
entity |
| Predicate | taggedWith |
P51475
|
FINISHED |
| Object | Azure resource tags |
—
|
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: Azure resource tags | Statement: [Azure workloads, taggedWith, Azure resource tags]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: taggedWith Context triple: [Azure workloads, taggedWith, Azure resource tags]
-
A.
tagtIn
Indicates that one entity is tagged or labeled as being located within or associated with the interior of another entity.
-
B.
mentionedWith
Indicates that two entities are mentioned together or in close association within the same context, such as a document, sentence, or conversation.
-
C.
associatedWithLabel
chosen
Indicates that an entity is connected or related to a particular label or tag used to categorize or identify it.
-
D.
associatedWithText
Indicates that an entity has a contextual or semantic connection to a specific piece of text.
-
E.
hasTagmata
Indicates that an organism possesses distinct functional body regions (tagmata) into which its body is divided.
- 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_69f34919f300819092b541c6277cd68a |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c27c4a9081909dff89529e04cf52 |
completed | May 3, 2026, 3:35 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6eb32c8190bf405b2011fa48f7 |
completed | May 3, 2026, 3:01 a.m. |
Created at: May 1, 2026, 12:54 a.m.