Triple
T9027213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FSL |
E216076
|
entity |
| Predicate | associatedWithMarketSegment |
P16877
|
FINISHED |
| Object | automotive electronics |
—
|
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: automotive electronics | Statement: [FSL, associatedWithMarketSegment, automotive electronics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithMarketSegment Context triple: [FSL, associatedWithMarketSegment, automotive electronics]
-
A.
brandSegment
chosen
Indicates the specific market segment or customer group that a brand is targeted toward or associated with.
-
B.
isAssociatedWith
Indicates that there exists a connection, relationship, or involvement between two entities without specifying its exact nature.
-
C.
associatedWithSection
Indicates that one entity is linked or connected to a particular section within a larger structure or context.
-
D.
affiliateOfType
Indicates that an affiliate entity belongs to, or is categorized under, a specific type or classification.
-
E.
relatedMarket
Indicates that two markets are connected or associated, such that activity, conditions, or changes in one market are relevant to or influence the other.
- 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_69ca83a5fa88819088144801b4dd7245 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6a7eb5b881908ace0c3327f06161 |
completed | April 1, 2026, 12:44 a.m. |
| PD | Predicate disambiguation | batch_69cc5ee132f08190940749c7c522e4c1 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:07 p.m.