Triple
T33702412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teresa Agnes |
E863492
|
entity |
| Predicate | relationshipWithThomas |
P206645
|
FINISHED |
| Object | telepathic partner |
—
|
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: telepathic partner | Statement: [Teresa Agnes, relationshipWithThomas, telepathic partner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipWithThomas Context triple: [Teresa Agnes, relationshipWithThomas, telepathic partner]
-
A.
relationshipToTony
Indicates the specific type of relationship or connection that an entity has with Tony.
-
B.
relationToStephenI
Indicates a familial or social relationship that an entity has specifically with Stephen I.
-
C.
relationshipToHenry
Indicates the specific type of relationship or connection that an entity has to Henry.
-
D.
relationshipWithTomWambsgans
Indicates the existence and nature of a relationship or connection that an entity has with Tom Wambsgans.
-
E.
relationshipToTracyLord
Indicates the specific type of personal or social relationship an entity has with Tracy Lord.
- 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_69f3498723a08190ac034339cc78eade |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037e0953908190b2930b3c06a40129 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a0379f6c3308190b954f7810214ceed |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037e07fe4481909ca21eae7a941ee7 |
completed | May 12, 2026, 7:22 p.m. |
Created at: May 1, 2026, 1:43 a.m.