Triple
T3996276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black Maybe |
E87104
|
entity |
| Predicate | performer |
P1363
|
FINISHED |
| Object | Common |
E2160
|
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: Common | Statement: [Black Maybe, performer, Common]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Common Context triple: [Black Maybe, performer, Common]
-
A.
Common
chosen
Common is an American rapper, actor, and activist known for his socially conscious lyrics and influential role in conscious hip-hop.
-
B.
Comum
Comum, known today as Como, is an ancient town in northern Italy near Lake Como that was an important Roman settlement and later a notable medieval and Renaissance center.
-
C.
Commons
Commons is the commonly used abbreviated name for the House of Commons, the lower house of the Parliament of the United Kingdom.
-
D.
Normal
Normal is a central Illinois town best known as the home of Illinois State University and part of the twin-city community with Bloomington.
-
E.
General
A General is a high-ranking military officer, typically commanding large units or formations and serving as one of the senior leaders within an armed force.
- 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_69aed94118148190975e6aa4e554cde9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa2159d88190a01de8b038341916 |
completed | March 9, 2026, 4:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b54c3a64888190881c37e760a14f15 |
completed | March 14, 2026, 11:53 a.m. |
Created at: March 9, 2026, 3:34 p.m.