Triple
T3489148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeremy |
E73682
|
entity |
| Predicate | conflictSource |
P48690
|
FINISHED |
| Object | partners using Steve Harvey’s dating advice |
—
|
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: partners using Steve Harvey’s dating advice | Statement: [Jeremy, conflictSource, partners using Steve Harvey’s dating advice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conflictSource Context triple: [Jeremy, conflictSource, partners using Steve Harvey’s dating advice]
-
A.
conflictLocation
Indicates the place or geographic area where a conflict, dispute, or confrontation occurs or is centered.
-
B.
conflictIn
Indicates that one entity is involved in, associated with, or occurs within a particular conflict or dispute.
-
C.
conflictSpecific
Indicates a specific, concrete instance or type of conflict that exists between the related entities.
-
D.
conflictContext
Indicates the situational background or circumstances within which a conflict between entities occurs or is interpreted.
-
E.
conflictType
Indicates the specific kind or category of conflict that characterizes the relationship or interaction between entities.
- 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_69ad85cca8d4819088494e9f3340fab5 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbb92b3ac8190b8675f5a5e9d4408 |
completed | March 8, 2026, 6:10 p.m. |
| PD | Predicate disambiguation | batch_69adae0b34908190b2bb5766a2231f7a |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adb055ed2481908171effe28151cf9 |
completed | March 8, 2026, 5:22 p.m. |
Created at: March 8, 2026, 3:18 p.m.