Triple
T21481624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Thin Man film series |
E530006
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Asta |
—
|
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: Asta | Statement: [The Thin Man film series, mainCharacter, Asta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Asta Context triple: [The Thin Man film series, mainCharacter, Asta]
-
A.
Asta
chosen
Asta is the small wire fox terrier dog featured as the beloved pet and occasional comic relief in the classic detective film series "The Thin Man."
-
B.
Asta
Asta is a feminine given name most notably borne by pioneering Danish silent film actress Asta Nielsen.
-
C.
Zaya
Zaya is a central human character in the fantasy film "Gods of Egypt," known for her devotion to Bek and her pivotal role in motivating the gods' struggle against Set.
-
D.
Aladar
Aladar is the heroic iguanodon protagonist of Disney's 2000 animated film "Dinosaur," known for leading a herd to safety after a catastrophic meteor strike.
-
E.
Arleng
Arleng is an alternative name for the Karbi language spoken by the Karbi people of Northeast India.
- 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_69e0c45acc3881908e38d3f28964152b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea338f988190a3044f8d02a567fe |
completed | April 23, 2026, 9:45 a.m. |
Created at: April 16, 2026, 6:21 p.m.