Triple
T14527928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louis |
E340826
|
entity |
| Predicate | friendOf |
P8712
|
FINISHED |
| Object | Prince Naveen |
E802190
|
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: Prince Naveen | Statement: [Louis, friendOf, Prince Naveen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Prince Naveen Context triple: [Louis, friendOf, Prince Naveen]
-
A.
Prince Naveen
chosen
Prince Naveen is the charming, carefree prince from Disney’s "The Princess and the Frog," known for his transformation into a frog and eventual romance with Tiana.
-
B.
Prince Sameer
Prince Sameer is one of the children of Tanzanian singer and songwriter Ali Kiba.
-
C.
Prince Mahesh
Prince Mahesh is the popular nickname of Mahesh Babu, a leading Telugu film actor and producer known for his work in South Indian cinema.
-
D.
Prince Nanda
Prince Nanda was a half-brother of the Buddha and an early Buddhist monk known for his initial attachment to worldly pleasures before attaining spiritual realization.
-
E.
Prince Naseem
Prince Naseem is the ring name of Naseem Hamed, a flamboyant British former professional boxer renowned for his explosive knockout power and unorthodox style in the featherweight division.
- 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_69d822dac79c8190a84a073f3cbaced5 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dea051bc608190ad4d516c5e7bca43 |
completed | April 14, 2026, 8:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd94acd8288190a91bf09220126e13 |
completed | May 8, 2026, 7:45 a.m. |
Created at: April 10, 2026, 1:22 a.m.