Triple
T380456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WHATWG |
E8665
|
entity |
| Predicate | hasLicense |
P12714
|
FINISHED |
| Object | CC0 for specifications |
—
|
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: CC0 for specifications | Statement: [WHATWG, hasLicense, CC0 for specifications]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLicense Context triple: [WHATWG, hasLicense, CC0 for specifications]
-
A.
hasLegalInstrument
Indicates that there exists a formal legal document or instrument that establishes, governs, or records the relationship between the related entities.
-
B.
licenseBuiltAs
Indicates that one entity is constructed, configured, or deployed under the terms or identity of another entity’s license.
-
C.
hasLegalStatus
Indicates that an entity possesses a particular legal classification, recognition, or standing under law.
-
D.
cityOfLicense
Indicates the city in which an entity (typically a broadcast station or similar regulated service) is officially licensed or authorized to operate.
-
E.
licenseFamily
Indicates that one license belongs to, is derived from, or is categorized under a broader family or class of related licenses.
- F. None of above. chosen
Provenance (4 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_69a2e7f47dd08190a4e294ccbbe46cd4 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec2c95088190a603bb1ee076ebd6 |
completed | Feb. 28, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_69a2e964d4b481909290e474b0341e3c |
completed | Feb. 28, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69a2eae0bd7081908197bbf5c55fe647 |
completed | Feb. 28, 2026, 1:17 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.