Triple
T13079642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Human Be-In |
E310168
|
entity |
| Predicate | organizedBy |
P123
|
FINISHED |
| Object | Michael Bowen |
E320046
|
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: Michael Bowen | Statement: [Human Be-In, organizedBy, Michael Bowen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Bowen Context triple: [Human Be-In, organizedBy, Michael Bowen]
-
A.
Michael Bowen (various)
chosen
Michael Bowen is a name shared by multiple notable individuals across different fields, such as acting, art, and religion.
-
B.
Stan Bowles
Stan Bowles was a talented and charismatic English forward of the 1970s, best known for his flair, creativity, and cult-hero status in domestic football.
-
C.
John Hough
John Hough is a British film and television director best known for his work in horror and genre cinema during the 1970s and 1980s.
-
D.
Nigel Bowen
Nigel Bowen is a New Zealand local-body politician who serves as the mayor of the Timaru District in the South Island.
-
E.
John Bowman
John Bowman was a 19th-century American politician who served in a key statewide infrastructure and regulatory role in New York.
- 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_69d806a733548190989cfd4ce981ca33 |
completed | April 9, 2026, 8:05 p.m. |
| NER | Named-entity recognition | batch_69d98119cb7081908b78ffe83ec99851 |
completed | April 10, 2026, 11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6d60c603881909dff49f4356042b5 |
completed | May 3, 2026, 4:58 a.m. |
Created at: April 9, 2026, 9:01 p.m.