Triple
T9839964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lester Diamond |
E239195
|
entity |
| Predicate | relationshipTypeWithGingerMcKenna |
P90274
|
FINISHED |
| Object | abusive |
—
|
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 | Statement: [Lester Diamond, relationshipTypeWithGingerMcKenna, abusive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithGingerMcKenna Context triple: [Lester Diamond, relationshipTypeWithGingerMcKenna, abusive]
-
A.
hasPoliticalRelationshipWith
Indicates a political connection or association between two entities, such as alliances, rivalries, collaborations, or other forms of political interaction.
-
B.
relationshipTypeWith Alicia Johns
Indicates the specific type or nature of the relationship that an entity has with Alicia Johns.
-
C.
relationshipTypeWithStaceyColbert
Indicates the specific nature or category of relationship that an entity has with Stacey Colbert.
-
D.
relationshipDynamicWithStaceyColbert
Indicates a changing or evolving interpersonal relationship involving Stacey Colbert.
-
E.
relationshipWithKat Barton
Indicates the existence or nature of a relationship that an entity has with Kat Barton.
- 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_69ca84e3f0c48190ada72a65ebd50efd |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb34b045481908f89abd576aab497 |
completed | April 2, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69cd03e30bc08190816c0a6d29c21b0f |
completed | April 1, 2026, 11:39 a.m. |
| PDg | Predicate description generation | batch_69cd06abc9248190a506b64e9c516d03 |
completed | April 1, 2026, 11:51 a.m. |
Created at: March 30, 2026, 8:33 p.m.