Triple
T32987993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Display and Adjacent Markets |
E843999
|
entity |
| Predicate | isBusinessOf |
P175888
|
FINISHED |
| Object | Applied Materials, Inc. |
—
|
NE NERFINISHED |
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: Applied Materials, Inc. | Statement: [Display and Adjacent Markets, isBusinessOf, Applied Materials, Inc.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isBusinessOf Context triple: [Display and Adjacent Markets, isBusinessOf, Applied Materials, Inc.]
-
A.
hasBusiness
Indicates that one entity owns, operates, or is formally associated with a business entity.
-
B.
hasTypeOfBusinesses
Indicates that an entity is associated with or contains specific categories or kinds of businesses.
-
C.
hasBusinessIn
Indicates that one entity conducts, operates, or maintains business activities within the jurisdiction, location, or domain of another entity.
-
D.
hasBusinesses
Indicates that an entity owns, operates, or is associated with one or more businesses.
-
E.
hasBusinessTypeAlong
Indicates that a business or commercial entity located along a route, corridor, or area is associated with a specific type or category of business activity.
- 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_69f3494c6f9c8190a255409fce8b1d3b |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d74b20a48190900dda1014cc13a8 |
completed | May 3, 2026, 5:04 a.m. |
| PD | Predicate disambiguation | batch_69f6d26f27dc8190ae426a3e1573933e |
completed | May 3, 2026, 4:43 a.m. |
| PDg | Predicate description generation | batch_69f6d749e7f081909c8196898c4191ad |
completed | May 3, 2026, 5:04 a.m. |
Created at: May 1, 2026, 1:22 a.m.