Triple
T12940564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MONA |
E309624
|
entity |
| Predicate | owner |
P347
|
FINISHED |
| Object | David Walsh |
E312510
|
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: David Walsh | Statement: [MONA, owner, David Walsh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Walsh Context triple: [MONA, owner, David Walsh]
-
A.
David Walsh
chosen
David Walsh is an Australian professional gambler, art collector, and entrepreneur best known as the founder of Hobart’s provocative Museum of Old and New Art (MONA).
-
B.
David M. Walsh
David M. Walsh is an American cinematographer known for his work on numerous films, particularly comedies, during the 1970s and 1980s.
-
C.
David I. Walsh
David I. Walsh was an American Democratic politician from Massachusetts who served as both governor and U.S. senator and was influential in early 20th-century labor and public contract legislation.
-
D.
Timothy R. R. Walsh
Timothy R. R. Walsh is an academic chemist best known as the doctoral advisor of Nobel Prize–winning biochemist Roger Y. Tsien.
-
E.
Douglas Thomas
Douglas Thomas is a scholar of media, technology, and learning, known for his work on digital culture and co-authoring influential books on how play and games shape education.
- 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_69d7bdfa933c8190b5a27aa4a08a19b7 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97dca2ee88190b45fafe7d53c35c9 |
completed | April 10, 2026, 10:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c0ec7e8081909fcff6cff11a9337 |
completed | May 3, 2026, 3:28 a.m. |
Created at: April 9, 2026, 5:43 p.m.