Triple
T14374254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Legend |
E356433
|
entity |
| Predicate | successorBrandScope |
P113793
|
FINISHED |
| Object | global brand (Lenovo) |
—
|
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: global brand (Lenovo) | Statement: [Legend, successorBrandScope, global brand (Lenovo)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: successorBrandScope Context triple: [Legend, successorBrandScope, global brand (Lenovo)]
-
A.
successorBranding
Indicates that one brand has replaced or continued another brand as its subsequent or updated identity.
-
B.
successorPlatformBrand
Indicates that one platform brand directly follows and replaces another in a product or generational sequence.
-
C.
successorManufacturer
Indicates that one manufacturer has taken over, replaced, or continued the role or operations of another manufacturer as its successor.
-
D.
successorInMarket
Indicates that one entity has taken over or followed another in serving the same market or customer base.
-
E.
successorModel
Indicates that one model is the direct follow-up or replacement for another earlier model.
- F. None of above. chosen
Provenance (4 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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de9007184c8190aebb003cb6548cc8 |
completed | April 14, 2026, 7:05 p.m. |
| PD | Predicate disambiguation | batch_69de2a9cb3e081909f6b33fdd939bb9e |
completed | April 14, 2026, 11:53 a.m. |
| PDg | Predicate description generation | batch_69de2e07d1f88190bdcd20967e484718 |
completed | April 14, 2026, 12:07 p.m. |
Created at: April 10, 2026, 1:15 a.m.