Triple
T13993821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blake Fielder-Civil |
E336644
|
entity |
| Predicate | relationshipStatusWithAmyWinehouse |
P112079
|
FINISHED |
| Object | on-and-off |
—
|
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-and-off | Statement: [Blake Fielder-Civil, relationshipStatusWithAmyWinehouse, on-and-off]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipStatusWithAmyWinehouse Context triple: [Blake Fielder-Civil, relationshipStatusWithAmyWinehouse, on-and-off]
-
A.
relationshipStatusWithMichael
Indicates the type or state of the relationship that an entity currently has with Michael.
-
B.
relationshipWithAliceMorgan
Indicates that there exists some form of relationship or connection between an entity and Alice Morgan.
-
C.
hasRelationshipStatusWithJoanCrawford
Indicates that an entity has a specific relationship status with Joan Crawford.
-
D.
relationshipToTinaBordereau
Indicates the specific type of personal or professional relationship an entity has with Tina Bordereau.
-
E.
relationshipToAndrewWyke
Indicates the specific type of personal or social relationship an entity has with Andrew Wyke.
- 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_69d81c639e808190a0e4b4f3d31c6a59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2eb53f508190855cd69b8061dd77 |
completed | April 14, 2026, 12:10 p.m. |
| PD | Predicate disambiguation | batch_69dd465dfbc4819090d8c61fd572d35f |
completed | April 13, 2026, 7:39 p.m. |
| PDg | Predicate description generation | batch_69de01ed2098819088ec45069f6f2609 |
completed | April 14, 2026, 8:59 a.m. |
Created at: April 9, 2026, 10:19 p.m.