Triple
T30313247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Long, Long Trailer |
E770980
|
entity |
| Predicate | hasTrailerType |
P191430
|
FINISHED |
| Object | house trailer |
—
|
LITERAL 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: house trailer | Statement: [The Long, Long Trailer, hasTrailerType, house trailer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrailerType Context triple: [The Long, Long Trailer, hasTrailerType, house trailer]
-
A.
hasTrailerCar
Indicates that one vehicle is connected to and pulling another vehicle configured as a trailer car.
-
B.
trailerType
chosen
Indicates the specific kind or category of trailer associated with or used in relation to an entity.
-
C.
hasTrailingTruckType
Indicates that an entity is associated with a specific type of truck positioned at the rear or trailing end.
-
D.
hasSeparateTrailingTruck
Indicates that an entity is accompanied by a distinct, independently attached trailing truck or carriage rather than having it integrated into its main structure.
-
E.
hasTrailType
Indicates that an entity (such as a trail or route) is associated with a specific type or category of trail.
- F. None of above.
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_69f22488f224819081b0f3ec41ab975c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fe6739d4dc8190ae7505c089bbac29 |
completed | May 8, 2026, 10:44 p.m. |
| PD | Predicate disambiguation | batch_69fe6541dffc81909c66a61ba69f38fc |
completed | May 8, 2026, 10:35 p.m. |
Created at: April 29, 2026, 7:51 p.m.