Triple
T2172671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martin Scorsese |
E48459
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Hugo |
E138723
|
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: Hugo | Statement: [Martin Scorsese, notableWork, Hugo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hugo Context triple: [Martin Scorsese, notableWork, Hugo]
-
A.
Hugo
Hugo is a masculine given name of Germanic origin, commonly used in various European and Spanish-speaking countries.
-
B.
Hugo
chosen
Hugo is a 2011 fantasy adventure film directed by Martin Scorsese, acclaimed for its innovative use of 3D and its homage to early cinema and filmmaker Georges Méliès.
-
C.
The Wonder
The Wonder is a psychological period drama film in which Florence Pugh plays an English nurse sent to investigate a young Irish girl who appears to survive without eating.
-
D.
The Light
The Light is a notable work by the rapper Common, showcasing his introspective lyricism and soulful, jazz-influenced hip-hop style.
-
E.
Mill
Mill is a village in the Dutch province of North Brabant, known for its historical sites and rural character.
- 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_69a88aa3faa48190995b233af6525815 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbec98a648190907ef4c6cad916d3 |
completed | March 7, 2026, 5:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae58f6c8c8819081a06861f6133fe9 |
completed | March 9, 2026, 5:21 a.m. |
Created at: March 4, 2026, 7:45 p.m.