Triple
T16395521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ex-Factor |
E398169
|
entity |
| Predicate | performer |
P1363
|
FINISHED |
| Object | Lauryn Hill |
E90425
|
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: Lauryn Hill | Statement: [Ex-Factor, performer, Lauryn Hill]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lauryn Hill Context triple: [Ex-Factor, performer, Lauryn Hill]
-
A.
Lauryn Hill
chosen
Lauryn Hill is an American singer, rapper, songwriter, and producer renowned for her groundbreaking work with the Fugees and her influential solo album "The Miseducation of Lauryn Hill."
-
B.
Jill Scott
Jill Scott is an American singer-songwriter, poet, and actress known for her soulful neo-soul music and powerful, expressive vocals.
-
C.
Erykah Badu
Erykah Badu is an American singer, songwriter, and producer renowned as the “Queen of Neo Soul” for her influential blend of R&B, jazz, and hip-hop.
-
D.
Meshell Ndegeocello
Meshell Ndegeocello is an American singer-songwriter, bassist, and producer known for her genre-blending work in neo-soul, jazz, funk, and R&B.
-
E.
Lauren Michelle Hill
Lauren Michelle Hill is an American model and actress best known as a Playboy Playmate and for her appearances in various television shows and films.
- 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_69d87f2950248190bc8ad9b9bebdc8c8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e326462298819087091dc935f0f916 |
completed | April 18, 2026, 6:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004579d9a88190b353952c5c301e9f |
completed | May 10, 2026, 8:44 a.m. |
Created at: April 10, 2026, 5:08 a.m.