Triple
T5795949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Standard & Poor's |
E128508
|
entity |
| Predicate | formerParentCompany |
P5815
|
FINISHED |
| Object | McGraw-Hill |
E175368
|
NE 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: McGraw-Hill | Statement: [Standard & Poor's, formerParentCompany, McGraw-Hill]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: McGraw-Hill Context triple: [Standard & Poor's, formerParentCompany, McGraw-Hill]
-
A.
McGraw-Hill
chosen
McGraw-Hill is a major American educational publishing company known for producing textbooks and academic resources across a wide range of disciplines.
-
B.
Wiley
Wiley is a masculine given name, often associated with notable American figures such as aviator Wiley Post.
-
C.
W. H. Freeman and Company
W. H. Freeman and Company is an academic publishing house best known for producing influential college-level science and mathematics textbooks.
-
D.
Pearson
Pearson is a major British multinational publishing and education company known for its textbooks, assessments, and digital learning solutions worldwide.
-
E.
Prentice Hall
Prentice Hall is a major American educational and professional publishing company known for its textbooks and academic titles across a wide range of disciplines.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c00845ca68819081a2ce3ecca577f7 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02a9304b081909ea004902f4ca569 |
completed | March 22, 2026, 5:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0982ce0ac8190b9f12cedb66c5eb3 |
completed | March 23, 2026, 1:32 a.m. |
Created at: March 22, 2026, 3:51 p.m.