Triple
T14941539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luther McDonald |
E372541
|
entity |
| Predicate | relationshipToMac |
P94755
|
FINISHED |
| Object | abusive father |
—
|
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: abusive father | Statement: [Luther McDonald, relationshipToMac, abusive father]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToMac Context triple: [Luther McDonald, relationshipToMac, abusive father]
-
A.
relationshipToHumans
Indicates the nature or type of connection, association, or relevance that something has specifically with humans.
-
B.
relationshipToARP
Indicates a specified type of relationship or association that an entity has to an ARP (which may represent a particular person, program, plan, or reference point).
-
C.
relationshipToRelative
chosen
Indicates the specific familial connection or kinship role that one person has in relation to a particular relative.
-
D.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
-
E.
relationshipToState
Indicates a relationship or connection that an entity has with a particular state or governmental body.
- 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded68c1df0819084c0cd61b207d398 |
completed | April 15, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69de9a588c2c8190b1245a1c406f447c |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:38 a.m.