Triple
T30713057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VarioFlex rear seats |
E781942
|
entity |
| Predicate | targetUserNeed |
P171646
|
FINISHED |
| Object | flexible passenger and cargo combinations |
—
|
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: flexible passenger and cargo combinations | Statement: [VarioFlex rear seats, targetUserNeed, flexible passenger and cargo combinations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetUserNeed Context triple: [VarioFlex rear seats, targetUserNeed, flexible passenger and cargo combinations]
-
A.
targetConsumerNeed
Indicates that something is intended to address, satisfy, or be directed toward a specific need or requirement of a consumer.
-
B.
targetsUseCase
Indicates that one entity is aimed at or designed to address a particular use case associated with another entity.
-
C.
targetUserAction
Indicates that a specific user is the intended recipient or focus of a particular action performed within the system.
-
D.
targetInvestorNeed
Indicates that an action, product, or communication is specifically aimed at addressing or fulfilling an investor’s particular needs or requirements.
-
E.
hasUserNeed
chosen
Indicates that an entity is associated with, or requires fulfillment of, a specific user need.
- 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_69f224acd24481908ed5f96f0d69b5dd |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd553d7cb881908d243e7a9f30ac85 |
completed | May 8, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69fd514dcb1c81908333c70d7edd79c9 |
completed | May 8, 2026, 2:58 a.m. |
Created at: April 29, 2026, 8:35 p.m.