Triple
T6882793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goody Mob |
E158839
|
entity |
| Predicate | member |
P10
|
FINISHED |
| Object | T-Mo |
E416772
|
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: T-Mo | Statement: [Goody Mob, member, T-Mo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: T-Mo Context triple: [Goody Mob, member, T-Mo]
-
A.
T-Mo
chosen
T-Mo is an American rapper best known as a member of the Atlanta hip hop group Goodie Mob and the larger Dungeon Family collective.
-
B.
T-Com
T-Com is a telecommunications brand associated with Deutsche Telekom, known for providing mobile and fixed-line communication services and sponsoring major sports venues.
-
C.
MiMo
MiMo is a distinctive post-World War II Miami Modernist architectural style characterized by playful curves, glass, and futuristic motifs, especially prominent in Miami Beach.
-
D.
Mifi
Mifi is a department in Cameroon's West Region, serving as an administrative division with its own local governance and population centers.
-
E.
Telico
Telico is a small unincorporated community located in Ellis County, Texas.
- 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_69c688342f6c8190ad7eea6ba262db99 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d8e90c9481908d00634f67fa71f8 |
completed | March 27, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c748c79d2c819097462b4517dd76d7 |
completed | March 28, 2026, 3:19 a.m. |
Created at: March 27, 2026, 2:23 p.m.