Triple
T25523695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deacon Ernest Frye |
E639722
|
entity |
| Predicate | relationshipToReverendReubenGregory |
P190324
|
FINISHED |
| Object | antagonistic ally |
—
|
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: antagonistic ally | Statement: [Deacon Ernest Frye, relationshipToReverendReubenGregory, antagonistic ally]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToReverendReubenGregory Context triple: [Deacon Ernest Frye, relationshipToReverendReubenGregory, antagonistic ally]
-
A.
relationshipToGraceWinslow
Indicates the specific nature of a person or entity’s relationship to Grace Winslow.
-
B.
relationshipToBartholomew
Indicates the specific type of relationship or connection an entity has to the individual named Bartholomew.
-
C.
relationshipToRogerChillingworth
Indicates the specific interpersonal connection or role that one entity has in relation to Roger Chillingworth.
-
D.
relationshipToBenjy
Indicates the specific type of relationship or connection an entity has to Benjy.
-
E.
relationshipToAgnesAndTobias
Indicates the specific familial, social, or other relational connection that an entity has to the pair Agnes and Tobias considered together.
- 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_69e75dbf3f9c8190b3f2a75d1b75d127 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69fcc4b700748190ae00b21d09c96695 |
completed | May 7, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69fcb0f9d3d881908a049475182fb039 |
completed | May 7, 2026, 3:34 p.m. |
| PDg | Predicate description generation | batch_69fcc4b5f22c8190b8b256adbdc2570c |
completed | May 7, 2026, 4:58 p.m. |
Created at: April 21, 2026, 3:08 p.m.