Triple
T20164769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maybank (former) |
E491799
|
entity |
| Predicate | sponsorCompanyIndustry |
P33295
|
FINISHED |
| Object | banking |
—
|
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: banking | Statement: [Maybank (former), sponsorCompanyIndustry, banking]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sponsorCompanyIndustry Context triple: [Maybank (former), sponsorCompanyIndustry, banking]
-
A.
sponsorIndustry
chosen
Indicates that an entity acts as a sponsor for, or is financially or organizationally supporting, a particular industry or industrial sector.
-
B.
sponsorshipIndustry
Indicates a relationship where one entity sponsors another specifically within a given industry or sector context.
-
C.
supportedIndustry
Indicates that one entity provides backing, resources, or services to help sustain or advance a particular industry.
-
D.
targetCompanyIndustry
Indicates that a company operates within or is associated with a specified industry sector.
-
E.
sponsorType
Indicates the specific role or category of sponsorship that an entity provides in relation to another entity or event.
- 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_69da6266c6888190bc1a3ecf24814d34 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6684376408190a68890ab48fa5424 |
completed | April 20, 2026, 5:54 p.m. |
| PD | Predicate disambiguation | batch_69e55b0c11cc8190836d1eee5945f000 |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:35 p.m.