Triple
T1311659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Esek Hopkins |
E28004
|
entity |
| Predicate | hasRelativeRole |
P27845
|
FINISHED |
| Object | Stephen Hopkins was his brother |
—
|
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: Stephen Hopkins was his brother | Statement: [Esek Hopkins, hasRelativeRole, Stephen Hopkins was his brother]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelativeRole Context triple: [Esek Hopkins, hasRelativeRole, Stephen Hopkins was his brother]
-
A.
hasRelativeLocation
Indicates that one entity is positioned in space in relation to another entity’s location.
-
B.
hasAuxiliaryRole
Indicates that an entity serves in a supporting or secondary capacity to another entity or primary role.
-
C.
hasEquivalentRole
Indicates that two entities hold roles that are functionally the same or interchangeable in a given context.
-
D.
hasRelativeOccupation
Indicates that two people are related in such a way that one’s occupation is defined or characterized in relation to the other’s occupation.
-
E.
refersToRole
Indicates that one entity designates, mentions, or points to another entity specifically in its capacity as a role or position.
- 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_69a498532c3481909223b74af2e578df |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1560f888190bdd9107b08395e0b |
completed | March 1, 2026, 10:44 p.m. |
| PD | Predicate disambiguation | batch_69a4bee9e4a88190b22ab2ee831a23c9 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c15361c8819094b8171e780b5560 |
completed | March 1, 2026, 10:44 p.m. |
Created at: March 1, 2026, 7:55 p.m.