Triple
T12120714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rachel |
E288684
|
entity |
| Predicate | worksWith |
P398
|
FINISHED |
| Object | Lil |
unclear NED1
|
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: Lil | Statement: [Rachel, worksWith, Lil]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lil Context triple: [Rachel, worksWith, Lil]
-
A.
Lil
Lil is a key character in Cory Doctorow's science fiction novel "Down and Out in the Magic Kingdom," set in a reputation-based future society centered around a Disney World-like theme park.
-
B.
Lil
Lil is the nickname and given name of Lil Hardin Armstrong, a pioneering American jazz pianist, composer, and bandleader.
-
C.
LIL
LIL is the IATA airport code for Lille Airport, the main international airport serving the Lille metropolitan area in northern France.
-
D.
Lil Star
"Lil Star" is a soulful, melodic track by Kelis featuring CeeLo Green that blends R&B and pop influences with reflective, uplifting lyrics.
-
E.
Lil Reese
Lil Reese is an American rapper from Chicago known for his role in the drill music scene and collaborations with artists like Chief Keef and Lil Durk.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69d6ab4b5e4c81909950b17151eb0951 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d91577a03c81909add7a5d7324a648 |
completed | April 10, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f684172c81908b77daa243dc8ed8 |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 8, 2026, 9:49 p.m.