Triple
T2462650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ford Pro |
E54566
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object | Ford Pro Software |
E54566
|
NE FINISHED |
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: Ford Pro Software | Statement: [Ford Pro, hasComponent, Ford Pro Software]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ford Pro Software Context triple: [Ford Pro, hasComponent, Ford Pro Software]
-
A.
Ford Pro
chosen
Ford Pro is Ford Motor Company's global commercial vehicle and services division focused on trucks, vans, fleet management, and productivity solutions for business customers.
-
B.
Ford Learning Center
The Ford Learning Center is an educational facility within the Nelson-Atkins Museum of Art that hosts classes, workshops, and programs to support art learning for visitors of all ages.
-
C.
ECU
ECU is the three-letter ISO 3166-1 alpha-3 country code that uniquely identifies Ecuador in international standards and data systems.
-
D.
Ford platforms
Ford platforms are the underlying vehicle architectures developed by the Ford Motor Company to support multiple models sharing common structural and mechanical components.
-
E.
Ford Blue
Ford Blue is a Ford Motor Company division focused on traditional internal-combustion and hybrid vehicles, emphasizing the brand’s legacy nameplates and mainstream models.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ab49dee84c819096b50a0049c347ac |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd11f093c8190877db3026d430bd5 |
completed | March 7, 2026, 7:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aef0d561a081909310113658b98f12 |
completed | March 9, 2026, 4:09 p.m. |
Created at: March 6, 2026, 9:44 p.m.