Triple
T13222304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dale Dobson |
E314783
|
entity |
| Predicate | relationshipToAllison |
P108597
|
FINISHED |
| Object | romantic interest |
—
|
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: romantic interest | Statement: [Dale Dobson, relationshipToAllison, romantic interest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToAllison Context triple: [Dale Dobson, relationshipToAllison, romantic interest]
-
A.
relationshipToTracyLord
Indicates the specific type of personal or social relationship an entity has with Tracy Lord.
-
B.
relationshipToTony
Indicates the specific type of relationship or connection that an entity has with Tony.
-
C.
relationshipToHannah
Indicates the specific type of relationship or connection that an entity has to Hannah.
-
D.
relationshipToTess
Indicates the specific type of relationship or connection that an entity has to Tess.
-
E.
relationshipToLaurie
Indicates the specific type of relationship or connection that an entity has to Laurie.
- 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_69d806affc688190a25b6ccc588e9c72 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf74d708190a61d8ad938653b06 |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bc938f081909f123bdf1263ff7f |
completed | April 10, 2026, 11:46 p.m. |
| PDg | Predicate description generation | batch_69d98c959ba08190adf29dc0c4e1fca6 |
completed | April 10, 2026, 11:49 p.m. |
Created at: April 9, 2026, 9:18 p.m.