Triple
T11904108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Reeve's Tale |
E283229
|
entity |
| Predicate | relationshipToTheMiller'sTale |
P102155
|
FINISHED |
| Object | hostile response |
—
|
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: hostile response | Statement: [The Reeve's Tale, relationshipToTheMiller'sTale, hostile response]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToTheMiller'sTale Context triple: [The Reeve's Tale, relationshipToTheMiller'sTale, hostile response]
-
A.
relationshipToKingShahryar
Indicates the type or nature of a person's relationship to King Shahryar, such as familial, marital, or social connection.
-
B.
relationshipWithHumbertHumbert
Indicates that an entity has a specified type of personal, emotional, or social relationship with Humbert Humbert.
-
C.
literaryRelationship
Indicates a relationship between entities that are connected through literature, such as authorship, influence, adaptation, or other text-based associations.
-
D.
relationshipToIsabelArcher
Indicates the specific personal or social connection that an entity has to Isabel Archer.
-
E.
relationshipToSanchoPanza
Indicates the specific type of relationship or connection an entity has to Sancho Panza.
- 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_69d6ab2c07e88190ba13b0d21fd6cf33 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8e525460c81909d855048d9c799bf |
completed | April 10, 2026, 11:55 a.m. |
| PD | Predicate disambiguation | batch_69d8bb2fca4481909893f3428b0871ac |
completed | April 10, 2026, 8:56 a.m. |
| PDg | Predicate description generation | batch_69d8d399d58c81908dab572aa82426d7 |
completed | April 10, 2026, 10:40 a.m. |
Created at: April 8, 2026, 9:44 p.m.