Triple
T36171996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adele August |
E1046166
|
entity |
| Predicate | relationshipTypeWithAnnAugust |
P10690
|
FINISHED |
| Object | mother-daughter |
—
|
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: mother-daughter | Statement: [Adele August, relationshipTypeWithAnnAugust, mother-daughter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithAnnAugust Context triple: [Adele August, relationshipTypeWithAnnAugust, mother-daughter]
-
A.
relationshipToAnne
Indicates the specific familial, social, or interpersonal connection that one entity has to Anne.
-
B.
relationshipStatusWithAnna
Indicates the type or state of the relationship that an entity currently has with Anna.
-
C.
relationshipWithAnse
Indicates that one entity has some form of relationship or connection with the entity named Anse.
-
D.
relationshipToAnnaPaul
Indicates that one entity has a specified personal or social relationship to Anna Paul.
-
E.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more entities.
- F. None of above.
Provenance (3 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_69f76e396bc88190b99d221bff9be27a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0a54cc8190868c1bfa1590d1a6 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:08 p.m.