Triple
T18896729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Hedges |
E462226
|
entity |
| Predicate | awardReceivedFor |
P107
|
FINISHED |
| Object | Oracle |
—
|
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: Oracle | Statement: [Michael Hedges, awardReceivedFor, Oracle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oracle Context triple: [Michael Hedges, awardReceivedFor, Oracle]
-
A.
Oracle
"Oracle" is a popular electronic dance music track by Australian DJ and producer Timmy Trumpet, known for its energetic festival sound and heavy drops.
-
B.
Oracle
Oracle is the codename of Barbara Gordon, a former Batgirl who becomes Batman’s expert hacker and information broker after being paralyzed by the Joker.
-
C.
Oracle
"Oracle" is a science fiction novel by British author Ian Watson, known for its imaginative exploration of advanced technology and human consciousness.
-
D.
Oracle
chosen
"Oracle" is a critically acclaimed acoustic guitar album by virtuoso musician Michael Hedges, showcasing his innovative fingerstyle technique and genre-blending compositions.
-
E.
Oracle Database
Oracle Database is a widely used enterprise relational database management system known for its scalability, reliability, and robust support for complex data workloads.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dcfd05bc819088903cca13cc2846 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c47f6c948190918ade08bb88f1fd |
completed | April 20, 2026, 6:15 a.m. |
Created at: April 10, 2026, 11:58 a.m.