Triple
T35531426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ethan Montgomery |
E1026808
|
entity |
| Predicate | relationshipTypeWithDog |
P96394
|
FINISHED |
| Object | lifelong companion |
—
|
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: lifelong companion | Statement: [Ethan Montgomery, relationshipTypeWithDog, lifelong companion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithDog Context triple: [Ethan Montgomery, relationshipTypeWithDog, lifelong companion]
-
A.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
-
B.
associatedWithAnimal
Indicates a relationship where an entity has a connection, link, or relevance to an animal.
-
C.
relationshipToCreature
chosen
Indicates a specified type of relational connection that one entity has toward a particular creature.
-
D.
regardsDogsAs
Indicates that one entity holds a particular attitude, view, or treatment toward dogs.
-
E.
relationshipToFelix
Indicates the specific type of relationship or connection that an entity has with Felix.
- 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_69f76dff7e508190b28ceeee770dce23 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a04d8348190a4819666eab42c9b |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:04 p.m.