Triple
T37155330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beadie Russell |
E920480
|
entity |
| Predicate | developsPersonalRelationshipWith |
P87667
|
FINISHED |
| Object | Jimmy McNulty |
—
|
NE NERFINISHED |
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: Jimmy McNulty | Statement: [Beadie Russell, developsPersonalRelationshipWith, Jimmy McNulty]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: developsPersonalRelationshipWith Context triple: [Beadie Russell, developsPersonalRelationshipWith, Jimmy McNulty]
-
A.
relationshipDevelopsWith
chosen
Indicates that a relationship grows, evolves, or becomes more developed between two entities over time.
-
B.
sexualRelationshipTo
Indicates that one entity has engaged in a sexual relationship or sexual activity with another entity.
-
C.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
-
D.
influencedByPersonalRelationshipWith
Indicates that one entity’s decisions, opinions, or actions are shaped or affected by a personal relationship it has with another entity.
-
E.
haveRelationshipWith
Indicates that one entity is in some form of defined relationship or association with another entity.
- F. None of above.
Provenance (3 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_69f76e9f87c08190b4c8f7fafbd8345a |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fddd373cdc8190be1b12e70e4deb1f |
completed | May 8, 2026, 12:55 p.m. |
| PD | Predicate disambiguation | batch_69fddc6915a88190ad41e379aa3ede13 |
completed | May 8, 2026, 12:51 p.m. |
Created at: May 3, 2026, 4:15 p.m.