Triple
T20481916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DB Class 430 |
E502475
|
entity |
| Predicate | safetySystem |
P840
|
FINISHED |
| Object |
Sifa
Sifa is a German train safety system that monitors driver alertness and automatically intervenes if the driver fails to respond.
|
E1434416
|
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: Sifa | Statement: [DB Class 430, safetySystem, Sifa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sifa Context triple: [DB Class 430, safetySystem, Sifa]
-
A.
Saber
Saber is a central heroic spirit and skilled swordswoman in the Fate/stay night: Unlimited Blade Works anime, known for her noble demeanor, chivalry, and iconic Excalibur.
-
B.
Scimitar
Scimitar is a type of curved, single-edged sword traditionally associated with Middle Eastern, South Asian, and North African cultures.
-
C.
Chain Sword
Chain Sword is a retractable, chain-linked blade weapon used by the Jaeger Gipsy Danger in the Pacific Rim universe for close-quarters combat against kaiju.
-
D.
Qatana
Qatana is a town in southwestern Syria that serves as an administrative center and lies near the capital, Damascus.
-
E.
Talwara
Talwara is a small town in the Indian state of Himachal Pradesh, known primarily for its proximity to the Pong Dam on the Beas River.
- 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: Sifa Triple: [DB Class 430, safetySystem, Sifa]
Generated description
Sifa is a German train safety system that monitors driver alertness and automatically intervenes if the driver fails to respond.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sifa Target entity description: Sifa is a German train safety system that monitors driver alertness and automatically intervenes if the driver fails to respond.
-
A.
Saber
Saber is a central heroic spirit and skilled swordswoman in the Fate/stay night: Unlimited Blade Works anime, known for her noble demeanor, chivalry, and iconic Excalibur.
-
B.
Scimitar
Scimitar is a type of curved, single-edged sword traditionally associated with Middle Eastern, South Asian, and North African cultures.
-
C.
Chain Sword
Chain Sword is a retractable, chain-linked blade weapon used by the Jaeger Gipsy Danger in the Pacific Rim universe for close-quarters combat against kaiju.
-
D.
Qatana
Qatana is a town in southwestern Syria that serves as an administrative center and lies near the capital, Damascus.
-
E.
Talwara
Talwara is a small town in the Indian state of Himachal Pradesh, known primarily for its proximity to the Pong Dam on the Beas River.
- 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_69e0b4af32848190aea80682b44d5d6e |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69b57fa9c819091d12320d46a0cee |
completed | April 20, 2026, 9:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0893ae04f481908da8206dfba0b463 |
completed | May 16, 2026, 3:56 p.m. |
| NEDg | Description generation | batch_6a0894c4c8b88190b2ac594477811c7b |
completed | May 16, 2026, 4:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08954be2688190a51911d6922a6413 |
completed | May 16, 2026, 4:03 p.m. |
Created at: April 16, 2026, 11:34 a.m.