Triple
T3130440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Internet |
E65396
|
entity |
| Predicate | drummer |
P15280
|
FINISHED |
| Object | Christopher Smith |
E338926
|
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: Christopher Smith | Statement: [The Internet, drummer, Christopher Smith]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christopher Smith Context triple: [The Internet, drummer, Christopher Smith]
-
A.
Christopher Smith
chosen
Christopher Smith is an individual associated with online communities or organizations connected to the Internet.
-
B.
Michael G. Smith
Michael G. Smith is an American Episcopal bishop who has served as the diocesan leader of the Episcopal Diocese of Albany.
-
C.
Phil Smith
Phil Smith was an American professional basketball player best known as a two-time NBA All-Star guard and key contributor to the Golden State Warriors’ 1975 championship team.
-
D.
Robert Paul Smith
Robert Paul Smith was an American author and playwright best known for his humorous novels and plays, including the work that inspired the romantic comedy "The Tender Trap."
-
E.
Mark L. Smith
Mark L. Smith is an American screenwriter best known for his work on intense genre films, including co-writing the Oscar-winning survival drama "The Revenant."
- 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_69ad8581c25c8190b0d85ba9b9baa531 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada549aaa881908dcf92d20fa6f238 |
completed | March 8, 2026, 4:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b28e058d8c8190ae58d750ae4c2c0e |
completed | March 12, 2026, 9:57 a.m. |
Created at: March 8, 2026, 3:04 p.m.