Triple
T22719647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julius Edgar Lilienfeld |
E561824
|
entity |
| Predicate | hasSurname |
P18
|
FINISHED |
| Object | Lilienfeld |
—
|
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: Lilienfeld | Statement: [Julius Edgar Lilienfeld, hasSurname, Lilienfeld]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lilienfeld Context triple: [Julius Edgar Lilienfeld, hasSurname, Lilienfeld]
-
A.
Lilienfeld
chosen
Lilienfeld is a German-language surname most notably associated with physicist Julius Edgar Lilienfeld, an early pioneer of field-effect transistor concepts.
-
B.
Frauenthal
Frauenthal is a historic theater and cultural landmark in Muskegon, Michigan, known for hosting a wide range of performing arts events.
-
C.
Lilienblum
Lilienblum is a Jewish surname most notably associated with Moshe Leib Lilienblum, a prominent 19th-century Hebrew writer and early Zionist thinker.
-
D.
Lilienstein
Lilienstein is a prominent table mountain in Saxon Switzerland, Germany, known for its striking flat-topped silhouette above the Elbe River.
-
E.
Meyerhof
Meyerhof is a surname of German origin, notably borne by biochemist Otto Fritz Meyerhof, a Nobel laureate recognized for his work on muscle metabolism.
- 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_69e2454fc984819088213b58ee87a002 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f17910deb48190b38174e16868f3dd |
completed | April 29, 2026, 3:20 a.m. |
Created at: April 17, 2026, 3:19 p.m.