Triple
T27581504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CA Technologies |
E699595
|
entity |
| Predicate | employeeCountYear |
P63085
|
FINISHED |
| Object | 2018 |
—
|
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: 2018 | Statement: [CA Technologies, employeeCountYear, 2018]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employeeCountYear Context triple: [CA Technologies, employeeCountYear, 2018]
-
A.
numberOfEmployeesDate
chosen
Indicates the specific date on which the recorded number of employees for an entity is valid or measured.
-
B.
numberOfEmployeesAtPeak
Indicates the highest recorded count of employees that an entity had at any point in time.
-
C.
workYear
Indicates the specific year or span of years during which an entity (such as a person or organization) was engaged in work or employment.
-
D.
employsApproximateNumberOfPeople
Indicates that an entity employs a roughly estimated or approximate number of people, rather than an exact headcount.
-
E.
employedPeople
Indicates that there exists a relationship where people are currently working in jobs or positions, typically under an employer.
- 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_69ef6a4cb8b881909b3a8d630fd89df2 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f66c5c13808190887180099745673b |
completed | May 2, 2026, 9:27 p.m. |
| PD | Predicate disambiguation | batch_69f66abddc448190a488852f8abdeb2c |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 27, 2026, 2:02 p.m.