Triple
T10168170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | eSTREAM |
E235258
|
entity |
| Predicate | recommendedCipher |
P79908
|
FINISHED |
| Object |
HC-128
HC-128 is a software-oriented stream cipher designed for high-speed encryption and selected as one of the recommended algorithms in the eSTREAM project portfolio.
|
E845872
|
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: HC-128 | Statement: [eSTREAM, recommendedCipher, HC-128]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HC-128 Context triple: [eSTREAM, recommendedCipher, HC-128]
-
A.
HC-4
HC-4 is a model of Coast Guard aircraft used for maritime patrol, search and rescue, and related operational missions.
-
B.
TX-12
TX-12 is a United States congressional district in north-central Texas that includes much of Fort Worth and surrounding areas and elects a member to the U.S. House of Representatives.
-
C.
Lora
Lora is a feminine given name, often considered a variant of Laura, used in various cultures.
-
D.
T.128
T.128 is an ITU-T standard that defines the Remote Desktop Protocol used for sharing and controlling desktops over a network.
-
E.
H125
The H125 is a popular single-engine light utility helicopter widely used worldwide for missions such as aerial work, passenger transport, and law enforcement.
- 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: HC-128 Triple: [eSTREAM, recommendedCipher, HC-128]
Generated description
HC-128 is a software-oriented stream cipher designed for high-speed encryption and selected as one of the recommended algorithms in the eSTREAM project portfolio.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: HC-128 Target entity description: HC-128 is a software-oriented stream cipher designed for high-speed encryption and selected as one of the recommended algorithms in the eSTREAM project portfolio.
-
A.
HC-4
HC-4 is a model of Coast Guard aircraft used for maritime patrol, search and rescue, and related operational missions.
-
B.
TX-12
TX-12 is a United States congressional district in north-central Texas that includes much of Fort Worth and surrounding areas and elects a member to the U.S. House of Representatives.
-
C.
Lora
Lora is a feminine given name, often considered a variant of Laura, used in various cultures.
-
D.
T.128
T.128 is an ITU-T standard that defines the Remote Desktop Protocol used for sharing and controlling desktops over a network.
-
E.
H125
The H125 is a popular single-engine light utility helicopter widely used worldwide for missions such as aerial work, passenger transport, and law enforcement.
- 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_69ca84ceafd0819085828600e11bed6b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdec6f64a48190883aefce58a65ca6 |
completed | April 2, 2026, 4:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d300ebacb88190850cf2242309b6ba |
completed | April 6, 2026, 12:40 a.m. |
| NEDg | Description generation | batch_69d30255c7408190a56764f3d3f36ee2 |
completed | April 6, 2026, 12:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d30343f4b081909eb80c772f6847bd |
completed | April 6, 2026, 12:50 a.m. |
Created at: March 30, 2026, 9:10 p.m.