Triple
T7226371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katy |
E154789
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | MKT |
E154788
|
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: MKT | Statement: [Katy, abbreviation, MKT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MKT Context triple: [Katy, abbreviation, MKT]
-
A.
MKT
chosen
MKT was the reporting mark and common abbreviation for the Missouri–Kansas–Texas Railroad, a major regional railroad that served the south-central United States.
-
B.
MKG
MKG is the three-letter IATA airport code for Muskegon County Airport in Muskegon, Michigan, USA.
-
C.
MRK
MRK is the stock ticker symbol for Merck & Co., a major global pharmaceutical company known for developing prescription medicines, vaccines, and animal health products.
-
D.
HPMKT
HPMKT is the commonly used abbreviation for the High Point Market, one of the world’s largest home furnishings trade shows held in High Point, North Carolina.
-
E.
MAR
MAR is the three-letter ISO 3166-1 alpha-3 country code assigned to Morocco.
- 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_69c68811dd1c8190ac460bb39e64e1f0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6e9de21e081908f30700f6211c5ef |
completed | March 27, 2026, 8:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7e51b3ae88190b7d03aa59d6910f5 |
completed | March 28, 2026, 2:26 p.m. |
Created at: March 27, 2026, 2:54 p.m.