Triple
T25621925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coopers & Lybrand |
E642320
|
entity |
| Predicate | hadClientType |
P79955
|
FINISHED |
| Object | multinational corporations |
—
|
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: multinational corporations | Statement: [Coopers & Lybrand, hadClientType, multinational corporations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadClientType Context triple: [Coopers & Lybrand, hadClientType, multinational corporations]
-
A.
hasNotableClientType
chosen
Indicates that an entity has clients belonging to a particular notable or distinguished category or type.
-
B.
operatedForClientType
Indicates that an operation or service is performed specifically on behalf of, or tailored to, a particular type or category of client.
-
C.
clientOf
Indicates that one entity receives services or conducts business from another entity in a client–provider relationship.
-
D.
hadMembershipType
Indicates that an entity possessed or was assigned a specific type or category of membership.
-
E.
customerType
Indicates the classification or category assigned to a customer based on their characteristics, status, or relationship with a business.
- 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_69e77e7a96748190b10f2699041e4e43 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fa2121f4819082c5135147a0f0d9 |
completed | May 2, 2026, 1:20 p.m. |
| PD | Predicate disambiguation | batch_69f4a0f7c6008190ae8cee3e71e19b94 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 21, 2026, 5:05 p.m.