Triple
T22051965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lupin |
E544905
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Lupin Part 1 |
—
|
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: Lupin Part 1 | Statement: [Lupin, hasPart, Lupin Part 1]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lupin Part 1 Context triple: [Lupin, hasPart, Lupin Part 1]
-
A.
Lupin (TV series)
chosen
Lupin is a French mystery thriller series on Netflix, starring Omar Sy as a gentleman thief inspired by the classic Arsène Lupin novels.
-
B.
Lupin
Lupin is the surname of Remus Lupin, a werewolf and former Defence Against the Dark Arts professor in the Harry Potter series.
-
C.
Lupin
Lupin is a French mystery thriller television series, inspired by the Arsène Lupin novels, in which Omar Sy plays a gentleman thief seeking to avenge his father.
-
D.
Mirzapur
Mirzapur is a city in the Indian state of Uttar Pradesh, known for its carpet and brassware industries and its location on the banks of the Ganges River.
-
E.
Do Aur Do Paanch
Do Aur Do Paanch is a 1980 Hindi action-comedy film starring Shashi Kapoor and Amitabh Bachchan, known for its lighthearted story of rival thieves and its popular music.
- 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_69e11e32445c8190ab97089b48a130bb |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1285513fc8190b691e1f57085956f |
completed | April 28, 2026, 9:36 p.m. |
Created at: April 16, 2026, 8:26 p.m.