Triple
T32577146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlie Chan in Egypt |
E832675
|
entity |
| Predicate | filmSeriesCharacterCreatedBy |
P174612
|
FINISHED |
| Object | Earl Derr Biggers |
—
|
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: Earl Derr Biggers | Statement: [Charlie Chan in Egypt, filmSeriesCharacterCreatedBy, Earl Derr Biggers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmSeriesCharacterCreatedBy Context triple: [Charlie Chan in Egypt, filmSeriesCharacterCreatedBy, Earl Derr Biggers]
-
A.
filmSeriesProtagonistOf
Indicates that a character serves as the main recurring protagonist of a particular film series.
-
B.
filmCharacterOf
Indicates that a person or character is a character appearing in a specified film.
-
C.
filmCharacterVersionOf
Indicates that one character is a specific film adaptation or portrayal of another character originating from a different version or medium.
-
D.
literarySeriesCharacter
Indicates that a character appears in, is part of, or is associated with a particular literary series.
-
E.
relatedSeriesCharacter
Indicates that one character is connected to another by appearing in a related or associated series within the same broader narrative universe.
- 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_69f349289adc81909f4374a58ec35a39 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c63f57188190a67c787135fad0a4 |
completed | May 3, 2026, 3:51 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2c138481908afa3ee3e91f8900 |
completed | May 3, 2026, 3:12 a.m. |
| PDg | Predicate description generation | batch_69f6c2df27ec8190912ec8eb488836d0 |
completed | May 3, 2026, 3:37 a.m. |
Created at: May 1, 2026, 1:04 a.m.