Triple
T14158902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darnell Turner |
E350884
|
entity |
| Predicate | relationshipToDodgeHickey |
P113045
|
FINISHED |
| Object | father |
—
|
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: father | Statement: [Darnell Turner, relationshipToDodgeHickey, father]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToDodgeHickey Context triple: [Darnell Turner, relationshipToDodgeHickey, father]
-
A.
relationshipToDudley
Indicates the specific familial or social relationship that one entity has to the person named Dudley.
-
B.
relationshipToDeloris
Indicates the specific type of personal, familial, or social relationship that one entity has with the entity named Deloris.
-
C.
relationshipToHenry
Indicates the specific type of relationship or connection that an entity has to Henry.
-
D.
relationshipToDickieWinslow
Indicates the specific type of relationship or connection an entity has to Dickie Winslow.
-
E.
relationshipToTucker
Indicates the specific familial, social, or professional relationship that one entity has to Tucker.
- 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_69d8278775fc8190b0802d22ca2f495d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61377de48190a3470d28f0edd34a |
completed | April 14, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69de05b8434c81908c33b1b513463b12 |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de239a02e881909b0e2679487e4ab2 |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 10, 2026, 12:58 a.m.