Triple
T199007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ford Model T |
E4060
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Model T |
E4060
|
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: Model T | Statement: [Ford Model T, alsoKnownAs, Model T]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Model T Context triple: [Ford Model T, alsoKnownAs, Model T]
-
A.
Ford Model T
chosen
The Ford Model T is an early 20th-century automobile that revolutionized personal transportation by making cars affordable to the mass market through assembly-line production.
-
B.
DeSoto
DeSoto is a suburban city in the Dallas–Fort Worth metropolitan area in North Texas.
-
C.
Ford Mustang
The Ford Mustang is an iconic American sports car known for its powerful performance, distinctive styling, and central role in popular car culture since the 1960s.
-
D.
Hoover
Hoover is a surname most prominently associated with Herbert Hoover, the 31st president of the United States.
-
E.
Packard
Packard is a surname most prominently associated with David Packard, the American electrical engineer and co-founder of Hewlett-Packard.
- 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_69a254bca59881909a15e1496f1508c7 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a25bcb2c7c8190b0e031e93651182a |
completed | Feb. 28, 2026, 3:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a31c93aa348190a7555a8327f7ad99 |
completed | Feb. 28, 2026, 4:49 p.m. |
Created at: Feb. 28, 2026, 2:44 a.m.