Triple
T25049550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plastic Valley |
E627337
|
entity |
| Predicate | hasLargeCompanies |
P110112
|
FINISHED |
| Object | multinational plastics firms |
—
|
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 plastics firms | Statement: [Plastic Valley, hasLargeCompanies, multinational plastics firms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLargeCompanies Context triple: [Plastic Valley, hasLargeCompanies, multinational plastics firms]
-
A.
hasNumberOfCompanies
Indicates the quantitative relationship specifying how many companies are associated with a given entity.
-
B.
isMajorCompanyIn
Indicates that a company is a leading or dominant business entity within a specified country, region, or market.
-
C.
hasBusinesses
chosen
Indicates that an entity owns, operates, or is associated with one or more businesses.
-
D.
hadMajorCompany
Indicates that an entity previously owned, led, or was primarily associated with a major company.
-
E.
isOneOfLargestEmployers
Indicates that an entity ranks among the largest organizations in terms of the number of people it employs.
- 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_69e2ff2b4c80819087c916b2b16241b9 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f65f7731e4819099d5bd3d915ee266 |
completed | May 2, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f65c1f94ac8190bc6fbc7916fc0d82 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 18, 2026, 6:08 a.m.