Triple
T22444068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LoopBack |
E554821
|
entity |
| Predicate | version |
P3286
|
FINISHED |
| Object | LoopBack 4 |
—
|
NE NERFINISHED |
How this triple was built (2 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: LoopBack 4 | Statement: [LoopBack, version, LoopBack 4]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LoopBack 4 Context triple: [LoopBack, version, LoopBack 4]
-
A.
LoopBack
chosen
LoopBack is an open-source Node.js framework for building APIs and connecting them to backend data sources.
-
B.
StrongLoop
StrongLoop is a software company best known for its work on Node.js tools and frameworks, including previously maintaining the popular Express.js web application framework.
-
C.
Loop 1604
Loop 1604 is a major highway encircling much of San Antonio, Texas, serving as a key route for regional traffic and access to suburban districts and commercial areas.
-
D.
Loop 101
Loop 101 is a major freeway encircling much of the Phoenix metropolitan area, connecting numerous suburbs and serving as a key route for regional traffic.
-
E.
Loop 202
Loop 202 is a major freeway in the Phoenix, Arizona metropolitan area that forms part of the region’s beltway system, helping route traffic around the city.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e5113208190ab58c6b595f9d1d0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ae517208190924a7968723f55ef |
completed | April 29, 2026, 1:12 a.m. |
Created at: April 16, 2026, 8:47 p.m.