Triple
T13107094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Best Editing |
E310869
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | Best Direction |
E25000
|
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: Best Direction | Statement: [Best Editing, relatedTo, Best Direction]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Best Direction Context triple: [Best Editing, relatedTo, Best Direction]
-
A.
Best Direction of a Play
chosen
Best Direction of a Play is a Tony Award category that honors outstanding achievement in directing Broadway plays.
-
B.
Best Director
Best Director is a Laurence Olivier Award category recognizing outstanding achievement in theatrical direction in London’s West End.
-
C.
Best Director
Best Director is a prestigious Academy Award recognizing outstanding achievement in film directing for a given year.
-
D.
Best Direction of a Musical
Best Direction of a Musical is a Tony Award category that honors outstanding achievement in directing Broadway musical productions.
-
E.
Best Foot Forward
Best Foot Forward is a 1941 Broadway musical comedy (later adapted into a film) known for its lively songs and lighthearted story about a prep-school boy and a Hollywood star.
- 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_69d806a872d08190a329806f8ff30df4 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98154c9f48190aeca779d97151759 |
completed | April 10, 2026, 11:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6e27a325c8190a5c0f1a582340078 |
completed | May 3, 2026, 5:51 a.m. |
Created at: April 9, 2026, 9:05 p.m.