Triple
T19549091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ThyssenKrupp AG |
E489151
|
entity |
| Predicate | tickerSymbol |
P1447
|
FINISHED |
| Object |
TKA
TKA is the stock ticker symbol for ThyssenKrupp AG, a major German industrial conglomerate known for its steel production, engineering, and technology services.
|
E1381979
|
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: TKA | Statement: [ThyssenKrupp AG, tickerSymbol, TKA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TKA Context triple: [ThyssenKrupp AG, tickerSymbol, TKA]
-
A.
TKA
TKA is the three-letter IATA airport code for Talkeetna Airport in Talkeetna, Alaska, a small regional hub often used for flightseeing tours to Denali.
-
B.
TKA
TKA is a regional vehicle registration code used on license plates for cars registered in the Kazimierza Wielka area of Poland.
-
C.
TKA
TKA is an American Latin freestyle music group best known for their late-1980s club and radio hits in the freestyle and dance-pop genres.
-
D.
THA
THA is the three-letter ISO 3166-1 alpha-3 country code representing Thailand.
-
E.
THA
THA is the National Rail station code for Thatcham railway station in Berkshire, England.
- 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: TKA Triple: [ThyssenKrupp AG, tickerSymbol, TKA]
Generated description
TKA is the stock ticker symbol for ThyssenKrupp AG, a major German industrial conglomerate known for its steel production, engineering, and technology services.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: TKA Target entity description: TKA is the stock ticker symbol for ThyssenKrupp AG, a major German industrial conglomerate known for its steel production, engineering, and technology services.
-
A.
TKA
TKA is a regional vehicle registration code used on license plates for cars registered in the Kazimierza Wielka area of Poland.
-
B.
TKA
TKA is the three-letter IATA airport code for Talkeetna Airport in Talkeetna, Alaska, a small regional hub often used for flightseeing tours to Denali.
-
C.
TKA
TKA is an American Latin freestyle music group best known for their late-1980s club and radio hits in the freestyle and dance-pop genres.
-
D.
THA
THA is the three-letter ISO 3166-1 alpha-3 country code representing Thailand.
-
E.
THA
THA is the National Rail station code for Thatcham railway station in Berkshire, England.
- 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63d2f39188190976e8b6b111499a0 |
completed | April 20, 2026, 2:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a074e8ab51481908a5f1a67643c0fd4 |
completed | May 15, 2026, 4:49 p.m. |
| NEDg | Description generation | batch_6a074fb48c348190ab6cb5571617b942 |
completed | May 15, 2026, 4:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a075092eaa08190bc8ec203bb8460a1 |
completed | May 15, 2026, 4:57 p.m. |
Created at: April 10, 2026, 1:41 p.m.