Triple
T12038854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KLAC |
E286608
|
entity |
| Predicate | hasSisterStation |
P15137
|
FINISHED |
| Object |
KRRL
KRRL is a radio station that operates as a sister outlet to KLAC, typically sharing ownership and complementary programming within the same broadcast market.
|
E961474
|
NE FINISHED |
How this triple was built (4 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: KRRL | Statement: [KLAC, hasSisterStation, KRRL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KRRL Context triple: [KLAC, hasSisterStation, KRRL]
-
A.
RKR
RKR is the vehicle registration code assigned to vehicles registered in the Rymanów area of Poland.
-
B.
KR
KR is the vehicle registration code used on license plates for the German city of Krefeld.
-
C.
KR
KR is the stock ticker symbol for The Kroger Co., one of the largest supermarket chains in the United States.
-
D.
KrU
KrU is the abbreviated name of the Committee on Cultural Affairs, a governmental body responsible for matters related to culture and cultural policy.
-
E.
KORL
KORL is the ICAO airport code for Orlando Executive Airport, a public airport serving the Orlando, Florida area.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: KRRL Triple: [KLAC, hasSisterStation, KRRL]
Generated description
KRRL is a radio station that operates as a sister outlet to KLAC, typically sharing ownership and complementary programming within the same broadcast market.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: KRRL Target entity description: KRRL is a radio station that operates as a sister outlet to KLAC, typically sharing ownership and complementary programming within the same broadcast market.
-
A.
RKR
RKR is the vehicle registration code assigned to vehicles registered in the Rymanów area of Poland.
-
B.
KR
KR is the vehicle registration code used on license plates for the German city of Krefeld.
-
C.
KR
KR is the stock ticker symbol for The Kroger Co., one of the largest supermarket chains in the United States.
-
D.
KrU
KrU is the abbreviated name of the Committee on Cultural Affairs, a governmental body responsible for matters related to culture and cultural policy.
-
E.
KORL
KORL is the ICAO airport code for Orlando Executive Airport, a public airport serving the Orlando, Florida area.
- F. None of above. chosen
Provenance (5 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_69d6ab4669e48190b59246358b0383ab |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9040a8be881908f4841145a7b4e86 |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f49d9937a08190b2f606a1e55733b5 |
completed | May 1, 2026, 12:33 p.m. |
| NEDg | Description generation | batch_69f53d9460bc8190869f2b7d095d98cb |
completed | May 1, 2026, 11:56 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f564b826ec819098906cf735e45093 |
completed | May 2, 2026, 2:43 a.m. |
Created at: April 8, 2026, 9:47 p.m.