Triple
T16483347
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kölner Haie |
E400376
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | KEC |
E400374
|
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: KEC | Statement: [Kölner Haie, shortName, KEC]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KEC Context triple: [Kölner Haie, shortName, KEC]
-
A.
KEC
chosen
KEC is the common abbreviation for Kölner Haie, a professional ice hockey club based in Cologne, Germany.
-
B.
KECP
KECP is the ICAO airport code for Northwest Florida Beaches International Airport, a commercial airport serving the Panama City, Florida area.
-
C.
KVS
KVS is the abbreviation for the Royal Society of Sciences in Uppsala, one of Sweden’s oldest scientific academies dedicated to advancing research and scholarship.
-
D.
KEH
KEH is the vehicle registration code used on license plates for vehicles registered in the Kelheim district of Bavaria, Germany.
-
E.
KLE Technological University
KLE Technological University is an engineering-focused higher education institution in Hubballi-Dharwad, Karnataka, known for its technical programs and research initiatives.
- 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_69d883813098819084f5409539723b59 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e0420ac81908f9a3548ddb3b1ff |
completed | April 18, 2026, 7:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00607aafa48190929250a879c602ca |
completed | May 10, 2026, 10:39 a.m. |
Created at: April 10, 2026, 5:13 a.m.