Triple
T1893765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IG Farben |
E41930
|
entity |
| Predicate | brokenUpInto |
P12217
|
FINISHED |
| Object | Hoechst |
E213164
|
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: Hoechst | Statement: [IG Farben, brokenUpInto, Hoechst]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hoechst Context triple: [IG Farben, brokenUpInto, Hoechst]
-
A.
Hoechst
chosen
Hoechst was a major German chemical and pharmaceutical company that later became part of the conglomerate IG Farben.
-
B.
Bayer
Bayer is a major German multinational pharmaceutical and life sciences company known for products such as aspirin and its work in healthcare and agriculture.
-
C.
Lonza
Lonza is a global Swiss-based life sciences company specializing in pharmaceutical, biotech, and nutrition products and services, particularly in contract development and manufacturing.
-
D.
Roche
Roche is a major Swiss multinational healthcare company and one of the world’s leading pharmaceutical and diagnostics firms.
-
E.
Rohm and Haas
Rohm and Haas is a specialty chemicals company known for producing advanced materials and chemical products used in coatings, electronics, and 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_69a8864b6de0819098d089f6a1b910a7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb7c376208190bbf28504f1aac881 |
completed | March 7, 2026, 5:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adfba6e94c8190ad1daafbe7f70a44 |
completed | March 8, 2026, 10:43 p.m. |
Created at: March 4, 2026, 7:34 p.m.