Triple
T5722435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gerd Binnig |
E126177
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Gerd |
E44323
|
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: Gerd | Statement: [Gerd Binnig, givenName, Gerd]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gerd Context triple: [Gerd Binnig, givenName, Gerd]
-
A.
Gerd
chosen
Gerd is a masculine given name of German origin, commonly used in German-speaking countries.
-
B.
Gerd
Gerd is a jötunn (giantess) in Norse mythology best known as the beautiful wife of the god Freyr, whose courtship of her is a central myth in the Norse canon.
-
C.
Boerhaave
Boerhaave is a Dutch surname most famously associated with Herman Boerhaave, an influential 18th-century physician and botanist often regarded as the father of clinical teaching.
-
D.
GUT
GUT is a leading technical university in Gdańsk, Poland, known for its engineering, technology, and research programs.
-
E.
Barrett
Barrett is a common English and Irish surname borne by numerous notable individuals across politics, law, sports, 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_69c0082f723881908ce8bb13a0c0f8b7 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c024e6c444819089270b188e60cc67 |
completed | March 22, 2026, 5:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c05a80aefc8190b6ea35ab405ea502 |
completed | March 22, 2026, 9:09 p.m. |
Created at: March 22, 2026, 3:46 p.m.