Triple
T29610631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Polly Prince |
E754706
|
entity |
| Predicate | relationshipDynamicWithReubenFeffer |
P203488
|
FINISHED |
| Object | contrasts his risk-averse personality |
—
|
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: contrasts his risk-averse personality | Statement: [Polly Prince, relationshipDynamicWithReubenFeffer, contrasts his risk-averse personality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipDynamicWithReubenFeffer Context triple: [Polly Prince, relationshipDynamicWithReubenFeffer, contrasts his risk-averse personality]
-
A.
relationshipToReverendReubenGregory
Indicates the nature of a person's relationship or connection to Reverend Reuben Gregory.
-
B.
relationshipTypeWithJoshSrebnick
Indicates the specific nature or category of the relationship that an entity has with Josh Srebnick.
-
C.
relationshipToRebecca
Indicates the specific type of relationship or connection an entity has to Rebecca.
-
D.
relationshipToPeter
Indicates the specific type of relationship or connection that an entity has to Peter.
-
E.
relationshipToPete
Indicates the specific type of relationship or connection that an entity has to Pete.
- 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_69f0ef85f62081909842b59fdf8717e1 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_6a019037edbc8190bdaec436ac2fcec6 |
completed | May 11, 2026, 8:15 a.m. |
| PD | Predicate disambiguation | batch_6a018fe05a34819080068f588b5ff80c |
completed | May 11, 2026, 8:14 a.m. |
| PDg | Predicate description generation | batch_6a0190370290819096183e9fb7d32cff |
completed | May 11, 2026, 8:15 a.m. |
Created at: April 28, 2026, 6:28 p.m.