Triple
T26618159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Shaft II |
E668121
|
entity |
| Predicate | relationshipToJohnShaft |
P197652
|
FINISHED |
| Object | nephew |
—
|
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: nephew | Statement: [John Shaft II, relationshipToJohnShaft, nephew]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToJohnShaft Context triple: [John Shaft II, relationshipToJohnShaft, nephew]
-
A.
relationshipToJackBrown
Indicates the specific familial, social, or professional relationship that an entity has to Jack Brown.
-
B.
relationshipToJack
Indicates the specific type of personal or social connection an entity has with Jack.
-
C.
relationshipToJohnShipton
Indicates the specific familial or social relationship that an entity has to John Shipton.
-
D.
relationshipToJamesBond
Indicates the specific familial, romantic, professional, or social relationship that one entity has to James Bond.
-
E.
relationshipToKlaatu
Indicates the specific familial, social, or professional relationship that one entity has to the entity named Klaatu.
- 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_69ee9cfe16088190a3dddd68e3c7b1ea |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69fea1f5d8c481908dc3351dc9ecef7f |
completed | May 9, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69fea06b6fe0819095bf4c1bc9809927 |
completed | May 9, 2026, 2:48 a.m. |
| PDg | Predicate description generation | batch_69fea1f4daa88190bd3cc1ace684e77f |
completed | May 9, 2026, 2:54 a.m. |
Created at: April 27, 2026, 2:19 a.m.