Triple
T15787411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rayber |
E382772
|
entity |
| Predicate | relationshipToFrancisMarionTarwater |
P120014
|
FINISHED |
| Object | uncle |
—
|
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: uncle | Statement: [Rayber, relationshipToFrancisMarionTarwater, uncle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToFrancisMarionTarwater Context triple: [Rayber, relationshipToFrancisMarionTarwater, uncle]
-
A.
relationshipToMissWatson
Indicates the type or nature of a person's relational connection to Miss Watson (e.g., familial, social, or other defined relationship).
-
B.
hasRelationshipTypeWith Tai Frasier
Indicates that there exists a specific type of relationship between an entity and Tai Frasier.
-
C.
relationshipWithMarinaMniszech
Indicates that an entity has a personal, political, or social relationship with Marina Mniszech.
-
D.
relationshipToArmandAubigny
Indicates the specific nature of the relationship an entity has with Armand Aubigny.
-
E.
relationshipToTinaBordereau
Indicates the specific type of personal or professional relationship an entity has with Tina Bordereau.
- 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_69d86da16e188190b89af699f1ed0bfe |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0540380448190a025338f0e62e6d1 |
completed | April 16, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69e00537bd1c81908d6e832792fd934f |
completed | April 15, 2026, 9:37 p.m. |
| PDg | Predicate description generation | batch_69e006b17f7881908b8c7a37f0af4581 |
completed | April 15, 2026, 9:44 p.m. |
Created at: April 10, 2026, 4:48 a.m.