Triple
T31226614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portia Charney |
E796155
|
entity |
| Predicate | hasRelationshipToAndrewMartin |
P203094
|
FINISHED |
| Object | confidante |
—
|
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: confidante | Statement: [Portia Charney, hasRelationshipToAndrewMartin, confidante]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelationshipToAndrewMartin Context triple: [Portia Charney, hasRelationshipToAndrewMartin, confidante]
-
A.
relationshipToMartinGray
Indicates the specific type of relationship or connection an entity has to Martin Gray.
-
B.
haveRelationshipWith
Indicates that one entity is in some form of defined relationship or association with another entity.
-
C.
relationshipToJohnAndrewLast
Indicates a familial or social relationship that an entity has specifically to John Andrew Last.
-
D.
hasRelationshipTypeWith Frank Drebin
Indicates that there exists a specific type of relationship between an entity and Frank Drebin.
-
E.
relationshipToAndrewWyke
Indicates the specific type of personal or social relationship an entity has with Andrew Wyke.
- 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_69f224da98f88190ab32f690cce5d303 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a011ee3507081908b42de4278ae0b83 |
completed | May 11, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_6a011e874420819091cac3f08e8aa3f9 |
completed | May 11, 2026, 12:10 a.m. |
| PDg | Predicate description generation | batch_6a011ee2a6408190b3b2763d01bac623 |
completed | May 11, 2026, 12:12 a.m. |
Created at: April 29, 2026, 9:10 p.m.