Triple
T8014011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ineos |
E186565
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object |
Andrew Currie
Andrew Currie is a British businessman best known as one of the key executives and co-founders behind the multinational chemicals company Ineos.
|
E707521
|
NE FINISHED |
How this triple was built (4 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: Andrew Currie | Statement: [Ineos, foundedBy, Andrew Currie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andrew Currie Context triple: [Ineos, foundedBy, Andrew Currie]
-
A.
Andrew Craigie
Andrew Craigie was an 18th-century American apothecary and the first Apothecary General of the U.S. Army during the Revolutionary War.
-
B.
Colin Buchanan
Colin Buchanan is an Anglican bishop and liturgical scholar who served as the Bishop of Woolwich in the Church of England.
-
C.
Iain Murray
Iain Murray is a machine learning researcher known for his contributions to probabilistic modeling and inference methods.
-
D.
Andrew McMillan
Andrew McMillan is a software developer and open-source contributor known for his work on email and groupware technologies, particularly with the Kolab groupware server.
-
E.
Doug Beattie
Doug Beattie is a Northern Irish politician and former British Army officer who serves as the leader of the Ulster Unionist Party (UUP).
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Andrew Currie Triple: [Ineos, foundedBy, Andrew Currie]
Generated description
Andrew Currie is a British businessman best known as one of the key executives and co-founders behind the multinational chemicals company Ineos.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Andrew Currie Target entity description: Andrew Currie is a British businessman best known as one of the key executives and co-founders behind the multinational chemicals company Ineos.
-
A.
Andrew Craigie
Andrew Craigie was an 18th-century American apothecary and the first Apothecary General of the U.S. Army during the Revolutionary War.
-
B.
Colin Buchanan
Colin Buchanan is an Anglican bishop and liturgical scholar who served as the Bishop of Woolwich in the Church of England.
-
C.
Iain Murray
Iain Murray is a machine learning researcher known for his contributions to probabilistic modeling and inference methods.
-
D.
Andrew McMillan
Andrew McMillan is a software developer and open-source contributor known for his work on email and groupware technologies, particularly with the Kolab groupware server.
-
E.
Doug Beattie
Doug Beattie is a Northern Irish politician and former British Army officer who serves as the leader of the Ulster Unionist Party (UUP).
- F. None of above. chosen
Provenance (5 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_69ca82abaffc8190ab8af79cdbc31ab3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3df0f4bc8190ae87586972018085 |
completed | March 31, 2026, 3:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc56b4608081909c546d56129d1164 |
completed | March 31, 2026, 11:20 p.m. |
| NEDg | Description generation | batch_69cc58ecd0608190ab0880992bc203fb |
completed | March 31, 2026, 11:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc5cb791b48190bd5004b518d23f84 |
completed | March 31, 2026, 11:45 p.m. |
Created at: March 30, 2026, 5:19 p.m.