Triple
T10902654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chemical Valley |
E257484
|
entity |
| Predicate | hasCompany |
P1287
|
FINISHED |
| Object | CF Industries |
E698513
|
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: CF Industries | Statement: [Chemical Valley, hasCompany, CF Industries]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CF Industries Context triple: [Chemical Valley, hasCompany, CF Industries]
-
A.
CF Industries
chosen
CF Industries is a leading North American manufacturer and distributor of nitrogen-based fertilizers for agricultural and industrial use.
-
B.
Holcim
Holcim is a global leader in innovative and sustainable building materials and construction solutions.
-
C.
Ineos
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.
-
D.
Chemours
Chemours is a U.S.-based chemical company known for producing performance chemicals and advanced materials, including the nonstick coating brand Teflon.
-
E.
Koppers
Koppers is an American industrial company historically known for producing coal tar chemicals, treated wood products, and materials for the steel and aluminum industries.
- 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_69d6aa8550c8819095508a2ed9acf3db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d761a4e9d48190b107839761a2152b |
completed | April 9, 2026, 8:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e1553bb88c8190b9730a31977e1dd1 |
completed | April 16, 2026, 9:31 p.m. |
Created at: April 8, 2026, 9:22 p.m.