Triple
T29562752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ford Five Hundred |
E750079
|
entity |
| Predicate | trunkSpaceEmphasis |
P5642
|
FINISHED |
| Object | large trunk |
—
|
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: large trunk | Statement: [Ford Five Hundred, trunkSpaceEmphasis, large trunk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trunkSpaceEmphasis Context triple: [Ford Five Hundred, trunkSpaceEmphasis, large trunk]
-
A.
trunkCharacteristic
Indicates a relationship where a specific characteristic or property is attributed to a trunk (such as that of a tree or similar object).
-
B.
trunkSymbolizes
Indicates that a trunk (such as that of a tree, elephant, or container) serves as a symbol or representation of some concept, quality, or entity.
-
C.
trunkVolume
chosen
Indicates the volume or capacity of an entity’s trunk or main storage compartment.
-
D.
hasTrunk
Indicates that one entity possesses or is equipped with a trunk as a physical feature or component.
-
E.
cargoSpace
Indicates that one entity provides storage capacity or room for carrying goods, equipment, or other items for another entity.
- 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_69f0bd4919e48190942b2a13d5b97d03 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f66d1e64e8819080579603e5bcdeb7 |
completed | May 2, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f6633ac8a88190ab0cda62bbfcf9b0 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 28, 2026, 5:21 p.m.