Triple
T3065814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tracks |
E62101
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Alexandre de Franceschi |
E490650
|
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: Alexandre de Franceschi | Statement: [Tracks, editedBy, Alexandre de Franceschi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alexandre de Franceschi Context triple: [Tracks, editedBy, Alexandre de Franceschi]
-
A.
Alexandre de Franceschi
chosen
Alexandre de Franceschi is a film editor known for his work on the movie "Lion."
-
B.
Armand Gensonné
Armand Gensonné was a French lawyer and revolutionary politician who became a prominent leader of the Girondin faction during the French Revolution and was executed during the Reign of Terror.
-
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.
Xavier Fabre
Xavier Fabre is a French architect known for designing prominent cultural venues, including the Mariinsky Concert Hall in Saint Petersburg.
-
E.
Robert Fraisse
Robert Fraisse is a French cinematographer known for his visually striking work on international films, including major war dramas and action features.
- 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_69ad85793e5c8190a358049bc4a98d8c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada0fc01dc81908fbdf7c1ef73afe4 |
completed | March 8, 2026, 4:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beb0a5d4908190bb817c48cb485088 |
completed | March 21, 2026, 2:52 p.m. |
Created at: March 8, 2026, 3:02 p.m.