Triple
T3066025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Slow West |
E62105
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object |
Roland Gallois
Roland Gallois is a film editor known for his work on the feature film "Slow West."
|
E494881
|
NE FINISHED |
How this triple was built (4 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: Roland Gallois | Statement: [Slow West, editedBy, Roland Gallois]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roland Gallois Context triple: [Slow West, editedBy, Roland Gallois]
-
A.
Gérard Lopez
Gérard Lopez is a Luxembourgish-Spanish businessman and investor known for owning and leading several European football clubs, including Girondins de Bordeaux and previously Lille OSC.
-
B.
Michel Andrault
Michel Andrault was a prominent French architect known for his influential large-scale housing and urban development projects in the late 20th century.
-
C.
Gérard de Battista
Gérard de Battista is a French cinematographer known for his work on numerous European films, including the acclaimed drama "Monsieur Ibrahim."
-
D.
Louis Boisot
Louis Boisot was a Dutch nobleman and admiral of the Sea Beggars who played a key role in the Dutch Revolt by helping to relieve the besieged city of Leiden in 1574.
-
E.
Thierry Cruanes
Thierry Cruanes is a computer scientist and entrepreneur best known as a co-founder of the cloud data warehousing company Snowflake.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Roland Gallois Triple: [Slow West, editedBy, Roland Gallois]
Generated description
Roland Gallois is a film editor known for his work on the feature film "Slow West."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Roland Gallois Target entity description: Roland Gallois is a film editor known for his work on the feature film "Slow West."
-
A.
Gérard Lopez
Gérard Lopez is a Luxembourgish-Spanish businessman and investor known for owning and leading several European football clubs, including Girondins de Bordeaux and previously Lille OSC.
-
B.
Michel Andrault
Michel Andrault was a prominent French architect known for his influential large-scale housing and urban development projects in the late 20th century.
-
C.
Gérard de Battista
Gérard de Battista is a French cinematographer known for his work on numerous European films, including the acclaimed drama "Monsieur Ibrahim."
-
D.
Louis Boisot
Louis Boisot was a Dutch nobleman and admiral of the Sea Beggars who played a key role in the Dutch Revolt by helping to relieve the besieged city of Leiden in 1574.
-
E.
Thierry Cruanes
Thierry Cruanes is a computer scientist and entrepreneur best known as a co-founder of the cloud data warehousing company Snowflake.
- F. None of above. chosen
Provenance (5 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_69ad85793e5c8190a358049bc4a98d8c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada0fd87308190918e7b616f033faa |
completed | March 8, 2026, 4:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beba392ad08190a66ccf58edecb722 |
completed | March 21, 2026, 3:33 p.m. |
| NEDg | Description generation | batch_69bebe2ca1cc8190bb7b5fb5b8fed9c7 |
completed | March 21, 2026, 3:50 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bebe8284d08190be8e991246662481 |
completed | March 21, 2026, 3:51 p.m. |
Created at: March 8, 2026, 3:02 p.m.