Triple
T37375380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacob Snell |
E927964
|
entity |
| Predicate | relationshipTypeWithDarleneSnell |
P205869
|
FINISHED |
| Object | volatile partnership |
—
|
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: volatile partnership | Statement: [Jacob Snell, relationshipTypeWithDarleneSnell, volatile partnership]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithDarleneSnell Context triple: [Jacob Snell, relationshipTypeWithDarleneSnell, volatile partnership]
-
A.
relationshipTypeWith Larry Darrell
Indicates the specific type or nature of the relationship that an entity has with Larry Darrell.
-
B.
relationshipToDeloris
Indicates the specific type of personal, familial, or social relationship that one entity has with the entity named Deloris.
-
C.
relationshipTypeWith Dolly Talbo
Indicates the specific nature or category of the relationship that an entity has with Dolly Talbo.
-
D.
relationshipTypeWithMarnie
Indicates the specific nature or category of relationship that an entity has with Marnie.
-
E.
relationshipTypeWithSamMalone
Indicates the specific nature or category of relationship that an entity has with Sam Malone.
- 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_69f76eb820248190a5c395ca50ad002a |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a13a1308190a202df66f4781855 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c842b2c819082f1d2db995ac2eb |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:16 p.m.