Triple
T13188458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OGC Nice |
E313918
|
entity |
| Predicate | owner |
P347
|
FINISHED |
| Object | INEOS |
E186565
|
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: INEOS | Statement: [OGC Nice, owner, INEOS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: INEOS Context triple: [OGC Nice, owner, INEOS]
-
A.
Ineos
chosen
Ineos is a large multinational chemicals and energy company based in the United Kingdom, known for its extensive portfolio of petrochemical, oil, gas, and manufacturing operations worldwide.
-
B.
BASF
BASF is a major German chemical company and one of the world's largest producers of chemicals and related products.
-
C.
Arkema
Arkema is a French multinational specialty chemicals and advanced materials company known for its innovations in adhesives, coatings, and performance polymers.
-
D.
NOVA Chemicals
NOVA Chemicals is a major North American petrochemical company known for producing plastics and chemical products, with significant operations in Canada’s Chemical Valley industrial region.
-
E.
Lanxess
Lanxess is a German specialty chemicals company known for producing high-performance plastics, rubber, and chemical intermediates for various industrial 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_69d98c4d60688190b34e65bbb5d4c152 |
completed | April 10, 2026, 11:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6f5fc4b78819088ad32d74dfb9d0a |
completed | May 3, 2026, 7:15 a.m. |
Created at: April 9, 2026, 9:15 p.m.