Triple
T10353001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mason trucks |
E243927
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Mason |
E248231
|
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: Mason | Statement: [Mason trucks, namedAfter, Mason]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mason Context triple: [Mason trucks, namedAfter, Mason]
-
A.
Mason
Mason is the given first name of Red Cashion, the famed American NFL referee known for his exuberant "First down!" calls.
-
B.
Mason
Mason is a common English surname of occupational origin, historically referring to a stoneworker or builder.
-
C.
Mason
chosen
Mason was an early 20th-century American automobile marque produced under the Durant Motors company, known for manufacturing mid-priced cars during the 1920s.
-
D.
Mason
Mason is the central protagonist of the work "Vicious," around whom the story’s main conflicts and developments revolve.
-
E.
Mason
Mason is the central protagonist of "Soldiers of Fortune," around whom the story’s military-themed action and character development revolve.
- 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_69d381b22b8c8190aaed476be5f872a9 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e949b8e88190ad933399323aed73 |
completed | April 7, 2026, 11:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7fb749e0c819090aa63ebaada298e |
completed | April 9, 2026, 7:18 p.m. |
Created at: April 6, 2026, 11:57 a.m.