Triple
T36954740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tameem Antoniades |
E914158
|
entity |
| Predicate | companyTypeWorkedAt |
P90962
|
FINISHED |
| Object | independent game studio |
—
|
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: independent game studio | Statement: [Tameem Antoniades, companyTypeWorkedAt, independent game studio]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: companyTypeWorkedAt Context triple: [Tameem Antoniades, companyTypeWorkedAt, independent game studio]
-
A.
employerType
Indicates the classification or category of an employer in relation to the entity (e.g., public, private, nonprofit, self-employed).
-
B.
workAt
Indicates that an entity is employed by or performs work for a particular organization, company, or place.
-
C.
worksInOrganizationType
chosen
Indicates that an entity is employed by or performs work within an organization of a specified type (e.g., company, nonprofit, government agency).
-
D.
employmentType
Indicates the specific kind or category of employment relationship that exists between an individual and an employer (e.g., full-time, part-time, contract).
-
E.
employerIn
Indicates that one entity serves as the employer of another within a specified context, such as a location, organization, or time period.
- 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_69f76e8b28848190abd81fe7a7374910 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fd884cb2b48190b6acd473430d9e19 |
completed | May 8, 2026, 6:53 a.m. |
| PD | Predicate disambiguation | batch_69fd8709ca208190a8bab836f0156af5 |
completed | May 8, 2026, 6:47 a.m. |
Created at: May 3, 2026, 4:13 p.m.