Triple
T14009693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Romberg |
E337045
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | Mark Romberg |
E1079209
|
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: Mark Romberg | Statement: [Romberg, hasNotableBearer, Mark Romberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark Romberg Context triple: [Romberg, hasNotableBearer, Mark Romberg]
-
A.
Mark Romberg
chosen
Mark Romberg is an individual associated with the use or application of a system, tool, or concept referred to as Romberg.
-
B.
Mark Colenburg
Mark Colenburg is an American drummer and producer best known for his work in contemporary jazz, hip-hop, and neo-soul with artists such as Robert Glasper.
-
C.
Mark Rolston
Mark Rolston is an American character actor known for his intense roles in films such as Aliens, The Shawshank Redemption, and numerous genre and action movies.
-
D.
Mark Seelig
Mark Seelig is a musician and composer known for his work in ambient and shamanic music, often featuring overtone and devotional chanting.
-
E.
Mark Rosman
Mark Rosman is an American film and television director and screenwriter best known for his work on family and teen-oriented movies and series, including projects for Disney.
- 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_69d81c645c5c8190b1fd16a285a1b78a |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2ed44f90819099ad08c09c066b56 |
completed | April 14, 2026, 12:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdef5e0648190ace4ec1605968e30 |
completed | May 7, 2026, 6:50 p.m. |
Created at: April 9, 2026, 10:19 p.m.