Triple
T26305475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eddie Doling |
E661668
|
entity |
| Predicate | relationshipStatusWithJoeyPotter |
P196312
|
FINISHED |
| Object | on-again, off-again relationship |
—
|
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: on-again, off-again relationship | Statement: [Eddie Doling, relationshipStatusWithJoeyPotter, on-again, off-again relationship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipStatusWithJoeyPotter Context triple: [Eddie Doling, relationshipStatusWithJoeyPotter, on-again, off-again relationship]
-
A.
relationshipToPete
Indicates the specific type of relationship or connection that an entity has to Pete.
-
B.
relationshipToBenny
Indicates the specific type of personal or social relationship that an entity has with Benny.
-
C.
relationshipToJoeBuck
Indicates the specific familial, social, or professional relationship that one entity has to the person Joe Buck.
-
D.
relationshipToJosephCooper
Indicates the specific familial, social, or professional relationship that one entity has to Joseph Cooper.
-
E.
relationshipToPeter
Indicates the specific type of relationship or connection that an entity has to Peter.
- 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_69ee812dacfc81908484aade9120fba9 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69fe21b0cba48190b56c39e9f1c0eafa |
completed | May 8, 2026, 5:47 p.m. |
| PD | Predicate disambiguation | batch_69fe204576848190aecf204e2adba5dc |
completed | May 8, 2026, 5:41 p.m. |
| PDg | Predicate description generation | batch_69fe21afdc4c8190913ac4b55a9a5f52 |
completed | May 8, 2026, 5:47 p.m. |
Created at: April 26, 2026, 10:18 p.m.