Triple
T36782133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evelyn Williams |
E908801
|
entity |
| Predicate | relationshipStatusWithPatrickBateman |
P205043
|
FINISHED |
| Object | engaged |
—
|
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: engaged | Statement: [Evelyn Williams, relationshipStatusWithPatrickBateman, engaged]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipStatusWithPatrickBateman Context triple: [Evelyn Williams, relationshipStatusWithPatrickBateman, engaged]
-
A.
relationshipToPatsey
Indicates the nature or type of relationship an entity has with the person or entity named Patsey.
-
B.
relationshipToPatrickDennis
Indicates the specific familial, social, or professional relationship that one entity has to Patrick Dennis.
-
C.
relationshipToPatrick Zariakas
Indicates that one entity has a specified personal or social relationship to Patrick Zariakas.
-
D.
relationshipTypeWithDanielPlainview
Indicates the specific nature or category of relationship that an entity has with Daniel Plainview.
-
E.
relationshipToTinaBordereau
Indicates the specific type of personal or professional relationship an entity has with Tina Bordereau.
- 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_69f76e798aa08190ace31098d1b13e9f |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a0e039481908a4a2666f76c5363 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82f8c88190bd77a086023ac0e1 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:12 p.m.