Triple
T10763980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrew S. Tanenbaum |
E253905
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Tanenbaum |
E253905
|
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: Tanenbaum | Statement: [Andrew S. Tanenbaum, familyName, Tanenbaum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tanenbaum Context triple: [Andrew S. Tanenbaum, familyName, Tanenbaum]
-
A.
Tanenbaum
chosen
Tanenbaum is the surname of Andrew S. Tanenbaum, a prominent computer scientist known for his influential work on operating systems and computer networks.
-
B.
Dekker
Dekker is a Dutch-origin surname borne by various notable individuals across fields such as literature, sports, and entertainment.
-
C.
Tennenbaum
Tennenbaum is a Jewish-origin surname borne by various individuals, including the American writer Irving Stone.
-
D.
Robert Tanenbaum
Robert Tanenbaum is an American trial attorney, law professor, and author known for his crime and legal thrillers, including the popular Butch Karp series.
-
E.
Galvin
Galvin is a surname of Irish origin borne by various notable individuals in fields such as sports, business, and the arts.
- 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_69d6aa5f54f4819082d0bbcb6f8797e6 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d731a504948190943f0e27c0d891ed |
completed | April 9, 2026, 4:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de235fe7748190ba004f889da389ff |
completed | April 14, 2026, 11:22 a.m. |
Created at: April 8, 2026, 9:16 p.m.