Triple
T14507072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pam / Cassidy |
E340290
|
entity |
| Predicate | relationshipTypeWithRandy "The Ram" Robinson |
P114502
|
FINISHED |
| Object | complex emotional bond |
—
|
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: complex emotional bond | Statement: [Pam / Cassidy, relationshipTypeWithRandy "The Ram" Robinson, complex emotional bond]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithRandy "The Ram" Robinson Context triple: [Pam / Cassidy, relationshipTypeWithRandy "The Ram" Robinson, complex emotional bond]
-
A.
relationshipTypeWithSamMalone
Indicates the specific nature or category of relationship that an entity has with Sam Malone.
-
B.
relationshipTypeWithRobertCohn
Indicates the specific nature or category of relationship that an entity has with Robert Cohn.
-
C.
relationshipTypeWith Eugene Gant
Indicates the specific nature or category of relationship that an entity has with Eugene Gant.
-
D.
relationshipTypeWithRobertAngier
Indicates the specific nature or category of relationship that an entity has with Robert Angier.
-
E.
relationshipWithBlondie
Indicates that there exists some form of relationship or connection between an entity and Blondie.
- 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_69d822d9c0408190b9a2b3643e58bb4d |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69de94e40e44819084f323f8f9982b75 |
completed | April 14, 2026, 7:26 p.m. |
| PD | Predicate disambiguation | batch_69de5c4ccba08190a988bfda0bc9f5cb |
completed | April 14, 2026, 3:25 p.m. |
| PDg | Predicate description generation | batch_69de5fb4de14819092acdecbd201d672 |
completed | April 14, 2026, 3:39 p.m. |
Created at: April 10, 2026, 1:21 a.m.