Triple
T14643522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donna Dixon |
E343784
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Ford Models |
E900056
|
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 Models | Statement: [Donna Dixon, employer, Ford Models]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ford Models Context triple: [Donna Dixon, employer, Ford Models]
-
A.
Ford Models
chosen
Ford Models is a prominent international modeling agency known for representing high-profile fashion models and shaping the modern modeling industry.
-
B.
Ford vehicles
Ford vehicles are a range of automobiles produced by the Ford Motor Company, including cars, trucks, SUVs, and commercial vehicles sold worldwide.
-
C.
Ford Ranges
Ford Ranges are a group of largely ice-covered mountain ranges in western Antarctica’s Marie Byrd Land, notable for their remote, rugged peaks and extensive glaciation.
-
D.
Ford EXP
The Ford EXP was a compact, two-seat sport hatchback produced by Ford in the 1980s as a sporty offshoot of the Escort line.
-
E.
Ford F-Series
The Ford F-Series is a long-running line of full-size pickup trucks that has become one of the best-selling and most iconic vehicle ranges in automotive history.
- 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_69d822e1a2cc81908e5bb93cf61ce3cc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb4e80aa48190884bab800f357106 |
completed | April 14, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdd5d404e881908d26e684702ae122 |
completed | May 8, 2026, 12:23 p.m. |
Created at: April 10, 2026, 1:26 a.m.