Triple
T15241973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kmart Corporation |
E364277
|
entity |
| Predicate | formerStockTicker |
P9230
|
FINISHED |
| Object | KM |
E364277
|
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: KM | Statement: [Kmart Corporation, formerStockTicker, KM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KM Context triple: [Kmart Corporation, formerStockTicker, KM]
-
A.
KM
chosen
KM is the stock ticker symbol formerly used to represent Kmart Corporation, a major American discount department store chain.
-
B.
KM
KM is the abbreviation for Kabataang Makabayan, a historic left-wing nationalist youth organization in the Philippines.
-
C.
KA
KA is the vehicle registration code used on license plates for cars registered in the German city of Karlsruhe.
-
D.
KA
KA is a postcode area in the United Kingdom covering parts of southwest Scotland, including towns such as Kilmarnock and Irvine.
-
E.
KA
KA is the IATA airline designator for Cathay Dragon, a former Hong Kong-based regional carrier owned by Cathay Pacific.
- 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_69d85a0dde7481908fc64d1e82d5d20d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e007dcc33081908545ea1a1d2c19fe |
completed | April 15, 2026, 9:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fedd41b7c48190917385c6c61370b2 |
completed | May 9, 2026, 7:07 a.m. |
Created at: April 10, 2026, 3:13 a.m.