Triple
T5691909
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yes |
E125445
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object | Patrick Moraz |
E202281
|
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: Patrick Moraz | Statement: [Yes, hasMember, Patrick Moraz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Patrick Moraz Context triple: [Yes, hasMember, Patrick Moraz]
-
A.
Patrick Moraz
chosen
Patrick Moraz is a Swiss keyboardist and composer best known for his work with the progressive rock bands Yes and The Moody Blues.
-
B.
Paul Grabowsky
Paul Grabowsky is an Australian pianist, composer, and bandleader renowned for his contributions to jazz and film music.
-
C.
Chuck Mangione
Chuck Mangione is an American flugelhorn player, composer, and bandleader best known for his smooth jazz hit "Feels So Good."
-
D.
Peter Sorg
Peter Sorg is a cinematographer best known for his work on Tim Burton’s 2012 stop-motion animated film "Frankenweenie."
-
E.
John Du Prez
John Du Prez is a British composer and musician best known for his film scores and long-running collaboration with the comedy group Monty Python.
- 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_69c0082bb19c8190823a4facd3cba79b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c023e500ec8190bfda4f6a818aa5dc |
completed | March 22, 2026, 5:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c05a4baea481908b4766888fd3edf1 |
completed | March 22, 2026, 9:08 p.m. |
Created at: March 22, 2026, 3:44 p.m.