Triple
T17022555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marketing Science |
E412981
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | MKS |
E412981
|
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: MKS | Statement: [Marketing Science, hasAbbreviation, MKS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MKS Context triple: [Marketing Science, hasAbbreviation, MKS]
-
A.
MKS
MKS is the London Stock Exchange ticker symbol for Marks & Spencer, a major British multinational retailer known for its clothing, home products, and food.
-
B.
MKS
chosen
MKS is the standard abbreviation for the academic journal "Marketing Science," which publishes research on quantitative and analytical approaches to marketing.
-
C.
Rockwell
Rockwell is the surname of Norman Rockwell, the iconic American painter and illustrator renowned for his depictions of everyday life in the United States.
-
D.
Rockwell
Rockwell is an American singer and songwriter best known for his 1984 hit single "Somebody's Watching Me."
-
E.
Rockwell
Rockwell is a Chicago Transit Authority 'L' station on the Brown Line located in the Lincoln Square neighborhood of Chicago.
- 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_69d886cc4170819093deddc7b8b4b6a7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d5d1d2e48190bbcba129247c6c2e |
completed | April 18, 2026, 7:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a011b4f9dfc819085639edb5cda1cca |
completed | May 10, 2026, 11:57 p.m. |
Created at: April 10, 2026, 5:33 a.m.