Triple
T28338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Creative Commons |
E565
|
entity |
| Predicate | operatesInArea |
P794
|
FINISHED |
| Object | copyright law |
—
|
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: copyright law | Statement: [Creative Commons, operatesInArea, copyright law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatesInArea Context triple: [Creative Commons, operatesInArea, copyright law]
-
A.
areaServed
Indicates the geographic region or jurisdiction within which a service, organization, or activity is provided or applicable.
-
B.
operatesWithin
chosen
Indicates that one entity carries out its activities, functions, or operations inside the scope, boundaries, or jurisdiction defined by another entity.
-
C.
operatesInSegment
Indicates that an entity conducts its activities or provides its services within a specified market or operational segment.
-
D.
usedInRegion
Indicates that something is utilized or applied within a specific geographic or administrative region.
-
E.
hasRegion
Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
- 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_69a2479dec388190967ba648663442c9 |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24925607c8190a9ce7ec834f3e5bb |
completed | Feb. 28, 2026, 1:47 a.m. |
| PD | Predicate disambiguation | batch_69a2486bd74c81908d32be3c7d22f51f |
completed | Feb. 28, 2026, 1:44 a.m. |
Created at: Feb. 28, 2026, 1:44 a.m.