Triple
T16673722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Half-Breed |
E405165
|
entity |
| Predicate | recordLabel |
P1500
|
FINISHED |
| Object | MCA |
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 | Statement: [Half-Breed, recordLabel, MCA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MCA Context triple: [Half-Breed, recordLabel, MCA]
-
A.
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.
-
B.
MCA
MCA is the UK government executive agency responsible for maritime safety, search and rescue coordination, and preventing pollution from ships in UK waters.
-
C.
MCA
MCA is the governing body of the Mohawk community of Akwesasne, responsible for local administration, services, and representation.
-
D.
MCA
MCA is a prominent Algerian football club based in Algiers, officially known as Mouloudia Club d'Alger.
-
E.
MCA
MCA is a postgraduate professional degree in computer applications that focuses on advanced software development, programming, and IT skills.
- 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_69d8838c28748190b3f5967c743940ab |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37d6904008190a79ab30b6d9ccae9 |
completed | April 18, 2026, 12:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a008a3ab8b481908b333b6a556a58d5 |
completed | May 10, 2026, 1:38 p.m. |
Created at: April 10, 2026, 5:19 a.m.