Triple
T8879944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abstract Wikipedia |
E211383
|
entity |
| Predicate | proposedBy |
P32
|
FINISHED |
| Object | Denny Vrandečić |
E194381
|
NE 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: Denny Vrandečić | Statement: [Abstract Wikipedia, proposedBy, Denny Vrandečić]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Denny Vrandečić Context triple: [Abstract Wikipedia, proposedBy, Denny Vrandečić]
-
A.
Denny Vrandečić
chosen
Denny Vrandečić is a Croatian computer scientist and Wikimedian best known for founding Wikidata and proposing the Wikifunctions project.
-
B.
Jure Leskovec
Jure Leskovec is a prominent computer scientist known for his influential work in data mining, social network analysis, and machine learning, particularly on large-scale graph data.
-
C.
Steve Staios
Steve Staios is a former NHL defenseman who transitioned into hockey management and now serves as an executive in the league.
-
D.
Andrew G. Myers
Andrew G. Myers is an American organic chemist renowned for his contributions to complex molecule synthesis and medicinal chemistry.
-
E.
Paul Resnick
Paul Resnick is an American academic and researcher known for his pioneering work in recommender systems, online communities, and human-computer interaction.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca838f9e20819096ab1f236a70381a |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc61677c9c8190aa09dc2a05d4cf95 |
completed | April 1, 2026, 12:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfabc1992481909e8a4216086d5111 |
completed | April 3, 2026, noon |
Created at: March 30, 2026, 6:52 p.m.