Triple
T21503413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FOCs |
E530535
|
entity |
| Predicate | includesExamplesSuchAs |
P100896
|
FINISHED |
| Object | Freightliner |
—
|
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: Freightliner | Statement: [FOCs, includesExamplesSuchAs, Freightliner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Freightliner Context triple: [FOCs, includesExamplesSuchAs, Freightliner]
-
A.
Freightliner
chosen
Freightliner is a major American manufacturer of heavy-duty and commercial trucks, best known for its long-haul semi-trucks and part of the Daimler AG family of brands.
-
B.
Freightliner eM2
The Freightliner eM2 is a battery-electric medium-duty truck designed for local and regional distribution with zero tailpipe emissions.
-
C.
Freightliner 122SD
The Freightliner 122SD is a heavy-duty vocational truck designed for severe-service applications such as construction, logging, and heavy hauling.
-
D.
Peterbilt
Peterbilt is an American manufacturer of premium heavy-duty and medium-duty trucks known for their durability, performance, and iconic styling.
-
E.
Mack Trucks
Mack Trucks is a historic American truck manufacturing company best known for its heavy-duty commercial vehicles and iconic bulldog logo.
- 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_69e0c45c81f08190a6b8bbb70a45aae7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea5deb388190a89a1f94285b7e55 |
completed | April 23, 2026, 9:46 a.m. |
Created at: April 16, 2026, 6:24 p.m.