Triple
T8135346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milo Tindle |
E189955
|
entity |
| Predicate | relationshipToAndrewWyke |
P81672
|
FINISHED |
| Object | wife’s lover |
—
|
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: wife’s lover | Statement: [Milo Tindle, relationshipToAndrewWyke, wife’s lover]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToAndrewWyke Context triple: [Milo Tindle, relationshipToAndrewWyke, wife’s lover]
-
A.
relationshipToAndrewCrockerHarris
Indicates that one entity has a specified personal or social relationship to Andrew Crocker Harris.
-
B.
relationshipToCatherine
Indicates the specific familial, social, or interpersonal connection that one entity has to the person named Catherine.
-
C.
relationshipToAnneBoleyn
Indicates the specific familial, marital, or social connection that an entity has to Anne Boleyn.
-
D.
relationshipToLaureyWilliams
Indicates the nature or type of relational connection an entity has specifically to Laurey Williams.
-
E.
relationshipToElizaWilliams
Indicates the specific nature of the relationship or connection that one entity has to Eliza Williams.
- 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_69ca82bcb4848190a9a9d036ad768642 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4c4c2e388190b86854f8b1765e61 |
completed | March 31, 2026, 4:23 a.m. |
| PD | Predicate disambiguation | batch_69cb3696379c8190a20965e59ed8f370 |
completed | March 31, 2026, 2:51 a.m. |
| PDg | Predicate description generation | batch_69cb4c496a8c81909aea840248d85d50 |
completed | March 31, 2026, 4:23 a.m. |
Created at: March 30, 2026, 5:35 p.m.