Triple
T10502713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ABT |
E247709
|
entity |
| Predicate | associatedCompanyCEOStartYear |
P53318
|
FINISHED |
| Object | 2020 |
—
|
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: 2020 | Statement: [ABT, associatedCompanyCEOStartYear, 2020]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedCompanyCEOStartYear Context triple: [ABT, associatedCompanyCEOStartYear, 2020]
-
A.
CEOStartYear
chosen
Indicates the calendar year in which an individual began serving as CEO of an organization.
-
B.
companyFoundedWith
Indicates that a company was established using or in association with a particular resource, organization, or founding context.
-
C.
foundedCompany
Indicates that an entity established or created a company, typically as its founder or co-founder.
-
D.
associatedCompanyFoundedIn
Indicates that the related company was founded in the specified year or time period.
-
E.
notableFounderLaterFounded
Indicates that an entity, already notable as a founder of something, subsequently went on to found another distinct entity at a later time.
- 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_69d381c4aa948190942e1d803143fb0e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5099c6a848190bf1d5361e9e61108 |
completed | April 7, 2026, 1:41 p.m. |
| PD | Predicate disambiguation | batch_69d4fb8e24ac8190912c9f11b8bd3084 |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:25 p.m.