Triple
T31699978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brewster's Millions (1935 film) |
E809026
|
entity |
| Predicate | workTitleDisambiguation |
P172970
|
FINISHED |
| Object | 1935 film adaptation of Brewster's Millions |
—
|
LITERAL 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: 1935 film adaptation of Brewster's Millions | Statement: [Brewster's Millions (1935 film), workTitleDisambiguation, 1935 film adaptation of Brewster's Millions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workTitleDisambiguation Context triple: [Brewster's Millions (1935 film), workTitleDisambiguation, 1935 film adaptation of Brewster's Millions]
-
A.
workTitleType
Indicates the specific category or type of a work’s title (e.g., main title, alternative title, translated title) in relation to that work.
-
B.
workTitle
Indicates the formal title or name of a work (such as a book, artwork, or composition) associated with an entity.
-
C.
workFromWhichTitleDerived
Indicates that a title is derived from, or based on, a particular underlying work.
-
D.
workTitleContains
Indicates that the title of a work includes a specified substring or term.
-
E.
workTitleReferences
Indicates that one work’s title explicitly mentions, cites, or alludes to another work.
- F. None of above. chosen
Provenance (4 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_69f348de914081909fc8edff56f34dbe |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6b2d9aad88190a445f8f591cb19fc |
completed | May 3, 2026, 2:28 a.m. |
| PD | Predicate disambiguation | batch_69f6b14faf608190a25b977c0740729c |
completed | May 3, 2026, 2:22 a.m. |
| PDg | Predicate description generation | batch_69f6b21da77081908c5c015c4606d344 |
completed | May 3, 2026, 2:25 a.m. |
Created at: April 30, 2026, 11:11 p.m.