Triple
T24691805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doosan Bears |
E611457
|
entity |
| Predicate | hasOfficialSocialMedia |
P156993
|
FINISHED |
| Object | YouTube |
—
|
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: YouTube | Statement: [Doosan Bears, hasOfficialSocialMedia, YouTube]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOfficialSocialMedia Context triple: [Doosan Bears, hasOfficialSocialMedia, YouTube]
-
A.
hasOfficialInstagram
Indicates that an entity possesses or is associated with an official Instagram account.
-
B.
hasOfficial
Indicates that an entity is formally associated with, represented by, or served by a designated official or office-holder.
-
C.
hasSocialService
Indicates that an entity provides, offers, or is associated with a social service to another entity or community.
-
D.
hasOfficialHashtag
Indicates that an entity is associated with a designated official hashtag used for identification or promotion.
-
E.
hasOfficialBlog
Indicates that an entity maintains or is associated with an officially recognized blog.
- 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_69e2c4d678b081908910f4271627a31a |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f410fe3b848190ae296a29f742ee30 |
completed | May 1, 2026, 2:33 a.m. |
| PD | Predicate disambiguation | batch_69f40ee8ada8819089a7016b50308ff0 |
completed | May 1, 2026, 2:24 a.m. |
| PDg | Predicate description generation | batch_69f410fc18808190b4e47d5a71d3a126 |
completed | May 1, 2026, 2:33 a.m. |
Created at: April 18, 2026, 3:20 a.m.