Triple
T13185202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Lubri-Graph Company |
E313831
|
entity |
| Predicate | originalNameOf |
P65
|
FINISHED |
| Object | Lubrizol |
E79843
|
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: Lubrizol | Statement: [The Lubri-Graph Company, originalNameOf, Lubrizol]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lubrizol Context triple: [The Lubri-Graph Company, originalNameOf, Lubrizol]
-
A.
Lubrizol
chosen
Lubrizol is a specialty chemicals company best known for producing additives and advanced materials used in lubricants, personal care products, and industrial applications.
-
B.
Lanxess
Lanxess is a German specialty chemicals company known for producing high-performance plastics, rubber, and chemical intermediates for various industrial applications.
-
C.
Chemours
Chemours is a U.S.-based chemical company known for producing performance chemicals and advanced materials, including the nonstick coating brand Teflon.
-
D.
BASF
BASF is a major German chemical company and one of the world's largest producers of chemicals and related products.
-
E.
Dow Corning Corporation
Dow Corning Corporation is a major American manufacturer specializing in silicone-based materials and technologies for industrial, consumer, and high-performance applications.
- 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_69d806ae1e08819090d95bfe1538cc17 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c4b663c8190b0b18f0785f7b57d |
completed | April 10, 2026, 11:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f70a2e415481908ad1036376f702dc |
completed | May 3, 2026, 8:41 a.m. |
Created at: April 9, 2026, 9:15 p.m.