Triple
T2907038
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tupolev Tu-134 |
E62789
|
entity |
| Predicate | ICAOTypeDesignator |
P16898
|
FINISHED |
| Object |
T134
T134 is the ICAO aircraft type designator assigned to the Soviet-era twin-engine jet airliner Tupolev Tu-134.
|
E310394
|
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: T134 | Statement: [Tupolev Tu-134, ICAOTypeDesignator, T134]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: T134 Context triple: [Tupolev Tu-134, ICAOTypeDesignator, T134]
-
A.
T-346A
T-346A is the Italian Air Force’s designation for the M-346 Master, an advanced jet trainer and light attack aircraft developed by Leonardo.
-
B.
R103
R103 is a regional road in South Africa that serves as an alternative route to the N3, connecting towns such as Ladysmith along the KwaZulu-Natal corridor.
-
C.
TX-14
TX-14 is a U.S. congressional district in Texas that elects a representative to the United States House of Representatives.
-
D.
T10
T10 is a technical committee under INCITS responsible for developing standards for SCSI (Small Computer System Interface) and related storage interfaces.
-
E.
T1300 train (historical)
The T1300 was a series of electric multiple-unit trains that operated on the Oslo Metro, serving as a key part of the system’s rolling stock during much of the 20th century.
- 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: T134 Triple: [Tupolev Tu-134, ICAOTypeDesignator, T134]
Generated description
T134 is the ICAO aircraft type designator assigned to the Soviet-era twin-engine jet airliner Tupolev Tu-134.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: T134 Target entity description: T134 is the ICAO aircraft type designator assigned to the Soviet-era twin-engine jet airliner Tupolev Tu-134.
-
A.
T-346A
T-346A is the Italian Air Force’s designation for the M-346 Master, an advanced jet trainer and light attack aircraft developed by Leonardo.
-
B.
R103
R103 is a regional road in South Africa that serves as an alternative route to the N3, connecting towns such as Ladysmith along the KwaZulu-Natal corridor.
-
C.
TX-14
TX-14 is a U.S. congressional district in Texas that elects a representative to the United States House of Representatives.
-
D.
T10
T10 is a technical committee under INCITS responsible for developing standards for SCSI (Small Computer System Interface) and related storage interfaces.
-
E.
T1300 train (historical)
The T1300 was a series of electric multiple-unit trains that operated on the Oslo Metro, serving as a key part of the system’s rolling stock during much of the 20th century.
- 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_69ab4c3e070c8190b78d3d2c005876dd |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abe0d0628c81909680af2f0db2ecae |
completed | March 7, 2026, 8:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b05612e79081908c962c2fe2e362d6 |
completed | March 10, 2026, 5:34 p.m. |
| NEDg | Description generation | batch_69b0622ea7b081908fe2029e61e21766 |
completed | March 10, 2026, 6:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b0630cd0348190882a4d3d90b217c3 |
completed | March 10, 2026, 6:29 p.m. |
Created at: March 6, 2026, 10:11 p.m.