Triple
T7687280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanenbaum Hall |
E174149
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Tanenbaum (namesake) |
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 (namesake) | Statement: [Tanenbaum Hall, namedAfter, Tanenbaum (namesake)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tanenbaum (namesake) Context triple: [Tanenbaum Hall, namedAfter, Tanenbaum (namesake)]
-
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.
Tomlinson
Tomlinson is a surname most notably associated with Ray Tomlinson, the American computer programmer credited with inventing networked email and introducing the "@" symbol in email addresses.
-
C.
Tjalling
Tjalling is a Dutch given name most notably borne by Nobel Prize–winning economist Tjalling C. Koopmans.
-
D.
Hufstedler
Hufstedler is the surname of Shirley Hufstedler, a prominent American judge and the first U.S. Secretary of Education.
-
E.
Tilghman
Tilghman is a masculine given name of English origin that has been borne by various notable American figures, including politicians and military officers.
- 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_69c6995840408190a19de6c51090f46f |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7022530e481908ba8d531bb915214 |
completed | March 27, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8a261019c8190b8ef53bfb611cef4 |
completed | March 29, 2026, 3:54 a.m. |
Created at: March 27, 2026, 4:02 p.m.