Triple
T12991098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Empress |
E321906
|
entity |
| Predicate | featuresArtist |
P1952
|
FINISHED |
| Object | Vegedream |
E1014203
|
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: Vegedream | Statement: [Empress, featuresArtist, Vegedream]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vegedream Context triple: [Empress, featuresArtist, Vegedream]
-
A.
Vegedream
chosen
Vegedream is a French-Ivorian singer and rapper best known for his Afrobeat-influenced urban pop hits, including the football anthem "Ramenez la coupe à la maison."
-
B.
VEGY
VEGY is the ICAO airport code for Gaya Airport, a public airport serving the city of Gaya in the Indian state of Bihar.
-
C.
Plenty
"Plenty" is a 1985 British drama film directed by Fred Schepisi, adapted from David Hare’s play about a former World War II resistance courier struggling to find meaning in postwar England.
-
D.
Plenty
Plenty is an indoor vertical farming company that uses advanced technology to grow produce more efficiently and sustainably.
-
E.
Ambrosia
Ambrosia is a figure from Greek mythology, known as a daughter of the Titan Atlas.
- 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_69d8076479b8819090afce3591939cdf |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e7765788190a9503ef055bc30ca |
completed | April 10, 2026, 10:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c0fca5e4819086b010fdd1813419 |
completed | May 3, 2026, 3:29 a.m. |
Created at: April 9, 2026, 8:43 p.m.