Triple
T32278578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Captain Allenby |
E824626
|
entity |
| Predicate | relationshipToCorry |
P206239
|
FINISHED |
| Object | sympathetic jailer |
—
|
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: sympathetic jailer | Statement: [Captain Allenby, relationshipToCorry, sympathetic jailer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToCorry Context triple: [Captain Allenby, relationshipToCorry, sympathetic jailer]
-
A.
relationshipToMacCory
Indicates the specific type of relationship or connection an entity has to MacCory.
-
B.
relationshipToCoraMunro
Indicates the specific type of personal or social relationship an entity has with Cora Munro.
-
C.
relationshipToPawneeNation
Indicates the specific type of familial, legal, historical, or political relationship that an entity has with the Pawnee Nation.
-
D.
relationshipToPaJoad
Indicates the specific familial or relational connection an entity has to the person Pa Joad.
-
E.
relationshipToTownship
Indicates the specific type of relationship or association that an entity has with a particular township.
- 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_69f3490f404081908450db66884f4334 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379edf2d88190b492fca86ed23cac |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7fb9f88190b384b1b68200aef0 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 12:43 a.m.