Triple
T38637572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | jQuery |
E937603
|
entity |
| Predicate | formerLicense |
P203348
|
FINISHED |
| Object | GNU General Public License |
—
|
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: GNU General Public License | Statement: [jQuery, formerLicense, GNU General Public License]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerLicense Context triple: [jQuery, formerLicense, GNU General Public License]
-
A.
formerLicensee
Indicates that an entity previously held a license from another entity but no longer does.
-
B.
previouslyLicensedAs
Indicates that an entity held a license under a different name or status at some earlier time.
-
C.
formerAccess
Indicates that an entity previously had access to another entity or resource but no longer does.
-
D.
former
Indicates that an entity previously held a role, status, or relationship but no longer does so in the present.
-
E.
formerCityOfLicense
Indicates that an entity previously held, but no longer holds, the official city of license designation for another entity (typically a broadcast station).
- 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_69f76ed5ca3c81909288f61fbf37b359 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a0164b052608190adc93240dad50a06 |
completed | May 11, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_6a01637fd3ac8190970eb09650d1e659 |
completed | May 11, 2026, 5:05 a.m. |
| PDg | Predicate description generation | batch_6a0164af262c8190876c9eb2421ad9a7 |
completed | May 11, 2026, 5:10 a.m. |
Created at: May 3, 2026, 4:32 p.m.