Triple
T4850228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Welding Institute |
E108395
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
TWI
TWI is a leading UK-based research and technology organization specializing in welding, joining, and related engineering technologies for industry.
|
E474914
|
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: TWI | Statement: [The Welding Institute, shortName, TWI]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TWI Context triple: [The Welding Institute, shortName, TWI]
-
A.
TWG
TWG is the commonly used abbreviation for The World Games, an international multi-sport event featuring disciplines not contested in the Olympic Games.
-
B.
TIJ
TIJ is the IATA airport code for Tijuana International Airport in Tijuana, Mexico.
-
C.
TWB
TWB is the IATA airport code for Toowoomba City Aerodrome, a regional airport serving the city of Toowoomba in Queensland, Australia.
-
D.
TI
TI is a technology company best known for designing and manufacturing calculators, semiconductors, and various electronic components.
-
E.
TUW
TUW is the commonly used abbreviation for the Vienna University of Technology, a major technical and scientific research university in Vienna, Austria.
- 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: TWI Triple: [The Welding Institute, shortName, TWI]
Generated description
TWI is a leading UK-based research and technology organization specializing in welding, joining, and related engineering technologies for industry.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: TWI Target entity description: TWI is a leading UK-based research and technology organization specializing in welding, joining, and related engineering technologies for industry.
-
A.
TWG
TWG is the commonly used abbreviation for The World Games, an international multi-sport event featuring disciplines not contested in the Olympic Games.
-
B.
TIJ
TIJ is the IATA airport code for Tijuana International Airport in Tijuana, Mexico.
-
C.
TWB
TWB is the IATA airport code for Toowoomba City Aerodrome, a regional airport serving the city of Toowoomba in Queensland, Australia.
-
D.
TI
TI is a technology company best known for designing and manufacturing calculators, semiconductors, and various electronic components.
-
E.
TUW
TUW is the commonly used abbreviation for the Vienna University of Technology, a major technical and scientific research university in Vienna, Austria.
- 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_69bd440a89548190a5f14ba6da6b97dc |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6d1e5cf08190bd6b6a524748f170 |
completed | March 20, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be5cdefda8819095fbc04446bf32f5 |
completed | March 21, 2026, 8:54 a.m. |
| NEDg | Description generation | batch_69be5dadcec88190bf9a272c4a9aef9a |
completed | March 21, 2026, 8:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be6159ff7c8190baa116240f76dea5 |
completed | March 21, 2026, 9:14 a.m. |
Created at: March 20, 2026, 1:25 p.m.