Triple
T10415982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PPG Industries |
E245516
|
entity |
| Predicate | hasBrand |
P1500
|
FINISHED |
| Object | PPG Paints |
E245516
|
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: PPG Paints | Statement: [PPG Industries, hasBrand, PPG Paints]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PPG Paints Context triple: [PPG Industries, hasBrand, PPG Paints]
-
A.
PPG Industries
chosen
PPG Industries is a global American company specializing in paints, coatings, and specialty materials for industrial, commercial, and consumer markets.
-
B.
PPG
PPG is the IATA airport code for Pago Pago International Airport, the main air gateway to American Samoa.
-
C.
BASF Coatings
BASF Coatings is a BASF subsidiary specializing in the development and production of automotive, industrial, and decorative coating solutions.
-
D.
Benjamin Moore
Benjamin Moore was an American Episcopal bishop and academic who served as the second bishop of New York and president of Columbia College in the early 19th century.
-
E.
Saint-Gobain
Saint-Gobain is a major French multinational corporation specializing in the production and distribution of construction materials and high-performance solutions for buildings and industry.
- 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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea108fec8190819423630888fa2b |
completed | April 7, 2026, 11:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d8dc2b06188190ad399e1b5a545aec |
completed | April 10, 2026, 11:16 a.m. |
Created at: April 6, 2026, 12:10 p.m.