Triple
T15237466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Theodore Thomas Orchestra |
E364164
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Theodore Thomas |
E364163
|
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: Theodore Thomas | Statement: [Theodore Thomas Orchestra, namedAfter, Theodore Thomas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Theodore Thomas Context triple: [Theodore Thomas Orchestra, namedAfter, Theodore Thomas]
-
A.
Theodore Thomas
chosen
Theodore Thomas was a prominent 19th-century German-American conductor who became a leading figure in U.S. orchestral music and helped establish Chicago as a major center for classical performance.
-
B.
George Lea
George Lea was a British Army officer and special forces commander best known for leading operations during the Borneo Confrontation in the 1960s.
-
C.
Max Whiteman
Max Whiteman is a person known primarily as the child of Dave Whiteman.
-
D.
Henry Wood
Henry Wood was an individual significant enough in local history or civic life that the city of Woodbury, New Jersey, was named in his honor.
-
E.
Leonard Wise
Leonard Wise is the writer whose work served as the basis for the film "Diggstown."
- 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_69d85a0dde7481908fc64d1e82d5d20d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e007da7e988190925a9b67b8070bc7 |
completed | April 15, 2026, 9:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fee5efb0108190b3b45e9917721354 |
completed | May 9, 2026, 7:44 a.m. |
Created at: April 10, 2026, 3:12 a.m.