Triple
T9210364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Lubey |
E221097
|
entity |
| Predicate | relationshipToKellers |
P86988
|
FINISHED |
| Object | friendly neighbor |
—
|
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: friendly neighbor | Statement: [Frank Lubey, relationshipToKellers, friendly neighbor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToKellers Context triple: [Frank Lubey, relationshipToKellers, friendly neighbor]
-
A.
relationshipToKateKeller
Indicates the specific familial, social, or interpersonal connection that one entity has to Kate Keller.
-
B.
relationshipToJoeKeller
Indicates the specific familial, social, or personal connection that one entity has to Joe Keller.
-
C.
relationshipToLarryKeller
Indicates the specific type of relationship or connection an entity has to Larry Keller.
-
D.
relationshipToChrisKeller
Indicates the specific type of personal or social relationship an entity has with Chris Keller.
-
E.
relationshipToLeeGates
Indicates the specific type of personal or professional relationship an entity has with Lee Gates.
- 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_69ca83e9d0e081908bdb71097201a06c |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd9b54520819087030148dadd6385 |
completed | April 1, 2026, 8:39 a.m. |
| PD | Predicate disambiguation | batch_69cc660af2408190ae06eb8326e1c64e |
completed | April 1, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69cc6745c17881908df72443e0800068 |
completed | April 1, 2026, 12:31 a.m. |
Created at: March 30, 2026, 7:27 p.m.