Triple
T33518852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe Roberts |
E858444
|
entity |
| Predicate | relationshipWithFrankRoberts |
P206502
|
FINISHED |
| Object | strained |
—
|
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: strained | Statement: [Joe Roberts, relationshipWithFrankRoberts, strained]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipWithFrankRoberts Context triple: [Joe Roberts, relationshipWithFrankRoberts, strained]
-
A.
relationshipTypeWithRobertCohn
Indicates the specific nature or category of relationship that an entity has with Robert Cohn.
-
B.
relationshipTypeWithRobertAngier
Indicates the specific nature or category of relationship that an entity has with Robert Angier.
-
C.
relationshipWithRobertBarone
Indicates a relationship or connection that an entity has with Robert Barone.
-
D.
relationshipStatusWithFrankTregear
Indicates the type or state of a person's relationship with Frank Tregear.
-
E.
relationshipToFrancis
Indicates the specific familial, social, or professional connection that an entity has with Francis.
- 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_69f349781c6c819082c516b260efe7e2 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f505c88190ac0879ab422c3054 |
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, 1:39 a.m.