Triple
T5252385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Hutchinson |
E118617
|
entity |
| Predicate | nationalityDuringLife |
P61750
|
FINISHED |
| Object | British subject |
—
|
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: British subject | Statement: [Thomas Hutchinson, nationalityDuringLife, British subject]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalityDuringLife Context triple: [Thomas Hutchinson, nationalityDuringLife, British subject]
-
A.
nationalityInText
Indicates that a person's nationality is mentioned or specified within a given text.
-
B.
nationalityInStory
Indicates that a character or entity in a narrative is associated with a particular nationality within the context of that story.
-
C.
nationalityInHumanWorld
Indicates that one entity has the specified national affiliation or citizenship within the context of the human world.
-
D.
nationalityInWorld
Indicates that an entity has a specific national affiliation or citizenship within the world context.
-
E.
originalNationality
Indicates the country or nationality an entity initially belonged to or originated from, before any later changes in citizenship or affiliation.
- 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_69bd446978108190bb5f9c5c23d93f88 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7b7cd7f4819098e591df07564a52 |
completed | March 20, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69bd77c30bac8190a883ca45da35d667 |
completed | March 20, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_69bd787975788190848ffbac87896efe |
completed | March 20, 2026, 4:40 p.m. |
Created at: March 20, 2026, 1:50 p.m.