Triple
T16491002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ebbe Munck |
E400566
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Ebbe |
E398803
|
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: Ebbe | Statement: [Ebbe Munck, givenName, Ebbe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ebbe Context triple: [Ebbe Munck, givenName, Ebbe]
-
A.
Ebbe
chosen
Ebbe is a given name commonly used as a short form or diminutive of the German name Eberhard.
-
B.
Ebb
Ebb is a surname most famously associated with American lyricist Fred Ebb, known for co-writing classic Broadway musicals such as "Cabaret" and "Chicago."
-
C.
Seama
Seama is a small unincorporated community in Cibola County, New Mexico, associated with the Laguna Pueblo.
-
D.
Erna
Erna is the given name of Erna Schneider Hoover, an American mathematician and pioneering computer scientist known for revolutionizing telephone switching systems.
-
E.
Eem
The Eem is a small river in the central Netherlands that flows through the city of Amersfoort before emptying into the Eemmeer.
- 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_69d883813098819084f5409539723b59 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e300a248190a3d4ca96a0a176cf |
completed | April 18, 2026, 7:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0058266b8c8190adc0974025553783 |
completed | May 10, 2026, 10:04 a.m. |
Created at: April 10, 2026, 5:13 a.m.