Triple
T5659423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bosnia and Herzegovina convertible mark |
E124698
|
entity |
| Predicate | symbol |
P129
|
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: [Bosnia and Herzegovina convertible mark, symbol, KM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KM Context triple: [Bosnia and Herzegovina convertible mark, symbol, KM]
-
A.
KM
chosen
KM is the stock ticker symbol formerly used to represent Kmart Corporation, a major American discount department store chain.
-
B.
KA
KA is the vehicle registration code used on license plates for cars registered in the German city of Karlsruhe.
-
C.
KE
KE is the IATA airline designator for Korean Air, the flag carrier and largest airline of South Korea.
-
D.
KE
KE is the two-letter ISO 3166-1 alpha-2 country code assigned to Kenya for international identification and data standards.
-
E.
KMGM
KMGM is the ICAO airport code for Montgomery Regional Airport, a public airport serving Montgomery, Alabama.
- 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_69c0082774a481909d7e63fb2aad56ac |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c0231e3c388190a2dd2c59b4a25881 |
completed | March 22, 2026, 5:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04da37ffc819095f33e7e66e7c1d0 |
completed | March 22, 2026, 8:14 p.m. |
Created at: March 22, 2026, 3:42 p.m.