Triple
T3420839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | iCalendar |
E72110
|
entity |
| Predicate | usesPropertySyntax |
P46693
|
FINISHED |
| Object | key-value pairs with parameters |
—
|
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: key-value pairs with parameters | Statement: [iCalendar, usesPropertySyntax, key-value pairs with parameters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesPropertySyntax Context triple: [iCalendar, usesPropertySyntax, key-value pairs with parameters]
-
A.
usesProp
chosen
Indicates that one entity employs, utilizes, or makes use of a particular property, resource, or object in performing an action or fulfilling a function.
-
B.
haveProperty
Indicates that an entity possesses, exhibits, or is characterized by a particular property or attribute.
-
C.
propUsed
Indicates that a particular property or attribute is utilized or applied in a given context or situation.
-
D.
requiresProperty
Indicates that one entity depends on another entity possessing a specific property or attribute in order for a condition, action, or relationship to hold.
-
E.
treatsAsProperty
Indicates that one entity regards or handles another entity as a property or attribute rather than as a distinct, independent object.
- 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_69ad85ad38e48190b7660c5118a35289 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb94eb9e8819087a525df4550914b |
completed | March 8, 2026, 6 p.m. |
| PD | Predicate disambiguation | batch_69adadfea024819094b41a13bc004bda |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:15 p.m.