Triple
T10859827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | O. J. Berman |
E256368
|
entity |
| Predicate | relationshipToHollyGolightly |
P96108
|
FINISHED |
| Object | former agent |
—
|
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: former agent | Statement: [O. J. Berman, relationshipToHollyGolightly, former agent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToHollyGolightly Context triple: [O. J. Berman, relationshipToHollyGolightly, former agent]
-
A.
relationshipToHenry
Indicates the specific type of relationship or connection that an entity has to Henry.
-
B.
relationshipToBertieWooster
Indicates the specific type of personal or social relationship an entity has with Bertie Wooster.
-
C.
relationshipToHannah
Indicates the specific type of relationship or connection that an entity has to Hannah.
-
D.
relationshipToKittyBennet
Indicates the specific type of personal or familial connection an entity has to Kitty Bennet.
-
E.
relationshipToLordEmsworth
Indicates the specific social or familial relationship that an entity has to Lord Emsworth.
- 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_69d6aa83d1448190a66d93c32394d21f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75150ceb88190a70356d12ce130c5 |
completed | April 9, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69d70d308dfc81908792f98cfb871392 |
completed | April 9, 2026, 2:21 a.m. |
| PDg | Predicate description generation | batch_69d7101c96708190808fef73199e8482 |
completed | April 9, 2026, 2:34 a.m. |
Created at: April 8, 2026, 9:20 p.m.