Triple
T1126875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S&P 100 |
E24738
|
entity |
| Predicate | includesCompaniesType |
P23265
|
FINISHED |
| Object | blue-chip companies |
—
|
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: blue-chip companies | Statement: [S&P 100, includesCompaniesType, blue-chip companies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesCompaniesType Context triple: [S&P 100, includesCompaniesType, blue-chip companies]
-
A.
includesPublicCompanies
Indicates that the referenced set, group, or collection contains one or more publicly traded companies as members.
-
B.
includesPrivateCompanies
Indicates that the relationship or set explicitly encompasses or applies to private companies as part of its scope.
-
C.
memberCompany
Indicates that a company is formally part of, or affiliated as a member with, a larger organization, group, or association.
-
D.
containsOrganizationType
chosen
Indicates that an entity includes or is associated with an organization of a specified organizational type (e.g., company, nonprofit, government agency).
-
E.
hasNumberOfCompanies
Indicates the quantitative relationship specifying how many companies are associated with a given entity.
- 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_69a4940712c88190aa244f3fc6070a65 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bc4bc21881909dcfe628f59f3e8c |
completed | March 1, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69a4bb4749ac8190b0fbddac2e9b2586 |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:44 p.m.