Triple
T23787070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tayo |
E587981
|
entity |
| Predicate | hasRelationshipTypeWithRocky |
P153573
|
FINISHED |
| Object | cousin |
—
|
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: cousin | Statement: [Tayo, hasRelationshipTypeWithRocky, cousin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelationshipTypeWithRocky Context triple: [Tayo, hasRelationshipTypeWithRocky, cousin]
-
A.
hasRelationshipTypeWithLukas
Indicates that an entity has a specific type of relationship or connection with Lukas.
-
B.
hasRelationshipTypeWithBenBoykewich
Indicates that an entity has a specific type of relationship or connection with Ben Boykewich.
-
C.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
-
D.
hasRelationshipTypeWithOmar
Indicates that an entity stands in a specified type of interpersonal or associative relationship with Omar.
-
E.
hasRelationshipTypeWith Valère
Indicates that an entity stands in a specific, characterized type of relationship with Valère.
- 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_69e2490f4ad48190b690878eec3596c6 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1c6321c5c819084db8f9ef0946326 |
completed | April 29, 2026, 8:49 a.m. |
| PD | Predicate disambiguation | batch_69f155fe300481909bd617443228df65 |
completed | April 29, 2026, 12:51 a.m. |
| PDg | Predicate description generation | batch_69f15adb23d88190ac2632299c26a9b3 |
completed | April 29, 2026, 1:11 a.m. |
Created at: April 17, 2026, 7:17 p.m.