Triple
T11620871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seidler Equity Partners |
E275632
|
entity |
| Predicate | targetCompanySize |
P23565
|
FINISHED |
| Object | middle market |
—
|
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: middle market | Statement: [Seidler Equity Partners, targetCompanySize, middle market]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetCompanySize Context triple: [Seidler Equity Partners, targetCompanySize, middle market]
-
A.
appliesToEmployerSize
Indicates that something (such as a rule, policy, or condition) is applicable only to employers of a specified size or within a defined employer size range.
-
B.
hasNumberOfCompanies
Indicates the quantitative relationship specifying how many companies are associated with a given entity.
-
C.
staffSize
chosen
Indicates the number of staff members associated with an entity.
-
D.
targetCompanies
Indicates that certain companies are the intended focus or recipients of a particular action, effort, or objective.
-
E.
employerNumberCharacteristic
Indicates a relationship where an entity is associated with a specific numeric characteristic that quantifies or identifies 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_69d6aaf84b548190ac072e4fb89ae18f |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a1206f1c81908d92024ef71958c0 |
completed | April 10, 2026, 7:05 a.m. |
| PD | Predicate disambiguation | batch_69d85dd6503c819081f9045e9d5c4f3f |
completed | April 10, 2026, 2:17 a.m. |
Created at: April 8, 2026, 9:39 p.m.