Triple
T19695091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Million-Year Picnic |
E472935
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | William Thomas |
—
|
NE NERFINISHED |
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: William Thomas | Statement: [The Million-Year Picnic, mainCharacter, William Thomas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: William Thomas Context triple: [The Million-Year Picnic, mainCharacter, William Thomas]
-
A.
William Thomas
William Thomas was a prominent 19th-century architect known for his influential work on major public monuments and buildings in Canada.
-
B.
William Thomas
William Thomas was an early settler and prominent figure in the Plymouth Colony town of Marshfield in 17th-century New England.
-
C.
William Thomas
William Thomas was a 16th-century English courtier, scholar, and political writer who served as a key advisor during the reign of Edward VI.
-
D.
William Thomas
chosen
William Thomas is an actor known for his role in the British television series "Mine All Mine."
-
E.
William Thomas
William Thomas is an actor best known for his role in the British television series "Twin Town."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e515bef88190bc30781aea50537a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6421385e88190b22b12ab3d851dea |
completed | April 20, 2026, 3:11 p.m. |
Created at: April 10, 2026, 1:46 p.m.