Triple
T8500720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lew Wasserman |
E201207
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | MCA Inc. |
E85483
|
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: MCA Inc. | Statement: [Lew Wasserman, employer, MCA Inc.]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MCA Inc. Context triple: [Lew Wasserman, employer, MCA Inc.]
-
A.
MCI Inc.
MCI Inc. was a major American telecommunications company and long-distance service provider that played a key role in breaking AT&T’s monopoly before eventually being acquired by Verizon.
-
B.
Marcus Corporation
Marcus Corporation is a U.S.-based company best known for its movie theatre and hospitality businesses, including operating cinema chains and hotels.
-
C.
MCA
MCA is the UK government executive agency responsible for maritime safety, search and rescue coordination, and preventing pollution from ships in UK waters.
-
D.
MCA
MCA is a postgraduate professional degree in computer applications that focuses on advanced software development, programming, and IT skills.
-
E.
MCA
chosen
MCA was a major American record label and entertainment company known for signing prominent artists and producing a wide range of popular music releases.
- 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_69ca831fe47c8190b5c57b456d2aefa0 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe5996ce88190956cb3f8d9ad3daf |
completed | March 31, 2026, 3:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce4e14c3d081908e98d5d7ad74716d |
completed | April 2, 2026, 11:08 a.m. |
Created at: March 30, 2026, 6:14 p.m.