Triple
T17510506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mi Plan |
E426435
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Salaam Remi |
—
|
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: Salaam Remi | Statement: [Mi Plan, producer, Salaam Remi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Salaam Remi Context triple: [Mi Plan, producer, Salaam Remi]
-
A.
Salaam Remi
chosen
Salaam Remi is an American record producer and songwriter best known for his work with artists like Amy Winehouse, Nas, and the Fugees, blending hip-hop, reggae, and soul influences.
-
B.
Sallah
Sallah is a jovial, resourceful Egyptian excavator and close ally of Indiana Jones who helps him navigate dangerous archaeological adventures.
-
C.
Remy
Remy is a fictional character portrayed as a family member of Brian Dennehy’s character Django.
-
D.
Remy
Remy is the ambitious, food-loving rat and main protagonist of Pixar’s animated film "Ratatouille," known for his exceptional culinary talent and dream of becoming a chef in Paris.
-
E.
Tammam Salam
Tammam Salam is a Lebanese politician who served as Prime Minister of Lebanon and has long been a prominent figure in the country’s political life.
- 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_69d889dd9164819087b1dc3c9240c870 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4525b03c48190ada74a7da0f4739c |
completed | April 19, 2026, 3:56 a.m. |
Created at: April 10, 2026, 5:48 a.m.