Triple
T36197982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sir Anthony Strallan |
E1047179
|
entity |
| Predicate | hasRelationshipTypeWith Lady Edith Crawley |
P204783
|
FINISHED |
| Object | broken engagement |
—
|
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: broken engagement | Statement: [Sir Anthony Strallan, hasRelationshipTypeWith Lady Edith Crawley, broken engagement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelationshipTypeWith Lady Edith Crawley Context triple: [Sir Anthony Strallan, hasRelationshipTypeWith Lady Edith Crawley, broken engagement]
-
A.
relationshipTypeWithBertieWooster
Indicates the specific nature or category of relationship an entity has with Bertie Wooster.
-
B.
relationTypeToHenryVIII
Indicates the specific type of relationship an entity has to Henry VIII (e.g., familial, political, or social connection).
-
C.
hasRelationshipTypeWithJimmyPorter
Indicates that an entity has a specific type of relationship or connection with Jimmy Porter.
-
D.
relationshipTypeWithGwendolenFairfax
Indicates the specific nature or category of relationship that an entity has with Gwendolen Fairfax.
-
E.
relationshipToEleanorVance
Indicates the specific nature or type of relationship an entity has with Eleanor Vance.
- 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_69f76e414bdc8190996f15a544220a3d |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0a54cc8190868c1bfa1590d1a6 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82f8c88190bd77a086023ac0e1 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:08 p.m.