Triple
T2194561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Company |
E49940
|
entity |
| Predicate | nicknameForRole |
P36689
|
FINISHED |
| Object | company that laid foundations of British rule in India |
—
|
LITERAL 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: company that laid foundations of British rule in India | Statement: [John Company, nicknameForRole, company that laid foundations of British rule in India]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nicknameForRole Context triple: [John Company, nicknameForRole, company that laid foundations of British rule in India]
-
A.
localNickname
Indicates that an entity is known by a particular nickname within a specific local or regional context.
-
B.
fandomNickname
Indicates that one entity is the nickname used by fans to refer to another entity (such as a person, group, or work).
-
C.
representsNickname
Indicates that one entity serves as a nickname or informal alternative name for another entity.
-
D.
honorificNickname
Indicates that one entity is referred to by a respectful or honorific nickname by another entity or in a given context.
-
E.
isNickname
Indicates that one name is an informal or alternative name commonly used to refer to the same person or entity as another name.
- F. None of above. chosen
Provenance (4 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_69a88aaba3c48190b351cab9b26989ff |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbf74147c81908793c3694894f94a |
completed | March 7, 2026, 6:02 a.m. |
| PD | Predicate disambiguation | batch_69abbda52328819089c7ab111bebb0ca |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abbea8bd4881908f72019a5acf6174 |
completed | March 7, 2026, 5:59 a.m. |
Created at: March 4, 2026, 7:46 p.m.