Triple
T2212415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panzer IV |
E50946
|
entity |
| Predicate | chassisUsedFor |
P7999
|
FINISHED |
| Object |
Nashorn
Nashorn was a German World War II tank destroyer armed with a powerful 88 mm gun and built on a modified Panzer IV chassis.
|
E245730
|
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: Nashorn | Statement: [Panzer IV, chassisUsedFor, Nashorn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nashorn Context triple: [Panzer IV, chassisUsedFor, Nashorn]
-
A.
SpiderMonkey
SpiderMonkey is Mozilla's open-source JavaScript engine, written in C/C++ and used primarily in the Firefox web browser.
-
B.
V8
V8 is a popular vegetable-based juice brand known for its blended vegetable and fruit beverages marketed as a nutritious drink option.
-
C.
V8
V8 is Google’s high-performance open-source JavaScript engine, used in Chrome and Node.js to compile and execute JavaScript directly to native machine code.
-
D.
JavaScriptCore
JavaScriptCore is Apple’s high-performance JavaScript engine used primarily in the Safari web browser and WebKit-based applications.
-
E.
HotSpot JVM
HotSpot JVM is a high-performance Java Virtual Machine known for its advanced just-in-time compilation and adaptive optimization techniques, originally developed by Sun Microsystems.
- 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: Nashorn Triple: [Panzer IV, chassisUsedFor, Nashorn]
Generated description
Nashorn was a German World War II tank destroyer armed with a powerful 88 mm gun and built on a modified Panzer IV chassis.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nashorn Target entity description: Nashorn was a German World War II tank destroyer armed with a powerful 88 mm gun and built on a modified Panzer IV chassis.
-
A.
SpiderMonkey
SpiderMonkey is Mozilla's open-source JavaScript engine, written in C/C++ and used primarily in the Firefox web browser.
-
B.
V8
V8 is a popular vegetable-based juice brand known for its blended vegetable and fruit beverages marketed as a nutritious drink option.
-
C.
V8
V8 is Google’s high-performance open-source JavaScript engine, used in Chrome and Node.js to compile and execute JavaScript directly to native machine code.
-
D.
JavaScriptCore
JavaScriptCore is Apple’s high-performance JavaScript engine used primarily in the Safari web browser and WebKit-based applications.
-
E.
HotSpot JVM
HotSpot JVM is a high-performance Java Virtual Machine known for its advanced just-in-time compilation and adaptive optimization techniques, originally developed by Sun Microsystems.
- 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_69a88b06709c8190978fb2418470d1b6 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abbfecea6c8190b762bbfda8490e31 |
completed | March 7, 2026, 6:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae655245c48190a37f4b6344a9a3dc |
completed | March 9, 2026, 6:14 a.m. |
| NEDg | Description generation | batch_69ae66579c008190876ce89581337293 |
completed | March 9, 2026, 6:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae668ef8bc819085ed1c83f447d396 |
completed | March 9, 2026, 6:19 a.m. |
Created at: March 4, 2026, 7:46 p.m.