Triple
T17586607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aissa |
E428337
|
entity |
| Predicate | relationshipTypeWithEdwardDouglas |
P128112
|
FINISHED |
| Object | emotional connection |
—
|
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: emotional connection | Statement: [Aissa, relationshipTypeWithEdwardDouglas, emotional connection]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithEdwardDouglas Context triple: [Aissa, relationshipTypeWithEdwardDouglas, emotional connection]
-
A.
relationshipToEdwardBloom
Indicates the nature or type of connection an entity has to Edward Bloom, such as familial, social, or other relational ties.
-
B.
relationshipTypeWith Eugene Gant
Indicates the specific nature or category of relationship that an entity has with Eugene Gant.
-
C.
relationshipToEdMercer
Indicates the type of personal or professional relationship an entity has with Ed Mercer.
-
D.
relationshipTypeWithDanielPlainview
Indicates the specific nature or category of relationship that an entity has with Daniel Plainview.
-
E.
relationshipTypeWithFrankUnderwood
Indicates the specific nature or category of relationship that an entity has with Frank Underwood.
- 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_69d889e1030481909950e140c63255b9 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e463d22f908190ae0f1eeafbe54459 |
completed | April 19, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fff0348190b899a32da537eaca |
completed | April 18, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69e3bbb50b448190a59dd4be33c76db7 |
completed | April 18, 2026, 5:13 p.m. |
Created at: April 10, 2026, 5:50 a.m.