Triple
T33602534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarah Lane |
E860756
|
entity |
| Predicate | relationshipTypeWithEddieLane |
P205231
|
FINISHED |
| Object | close personal connection |
—
|
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: close personal connection | Statement: [Sarah Lane, relationshipTypeWithEddieLane, close personal connection]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithEddieLane Context triple: [Sarah Lane, relationshipTypeWithEddieLane, close personal connection]
-
A.
relationshipToEddieDean
Indicates the specific type of relationship or connection an entity has to Eddie Dean.
-
B.
relationshipWithFastEddieFelson
Indicates that there exists some form of interpersonal relationship or connection between an entity and Fast Eddie Felson.
-
C.
relationshipTypeWithEdwardDouglas
Indicates the specific nature or category of relationship that an entity has with Edward Douglas.
-
D.
relationshipTypeWith Brian Flanagan
Indicates the specific nature or category of relationship that an entity has with Brian Flanagan.
-
E.
relationshipToEdd
Indicates the specific type of relationship or connection that an entity has to Edd.
- 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_69f3497f35908190a2e9bbb9b96c7a3f |
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_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:41 a.m.