Triple
T18820895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Annie James |
E460258
|
entity |
| Predicate | hasPetContext |
P99472
|
FINISHED |
| Object | lives in a household with a dog in London |
—
|
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: lives in a household with a dog in London | Statement: [Annie James, hasPetContext, lives in a household with a dog in London]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPetContext Context triple: [Annie James, hasPetContext, lives in a household with a dog in London]
-
A.
hasPetForm
Indicates that one entity can transform into or assume the form of another entity that is characterized as a pet.
-
B.
hasLocalContext
Indicates that something exists or occurs within a specific, surrounding situational or environmental context tied to a particular place or scope.
-
C.
hasPetTypeFocus
chosen
Indicates that an entity’s primary focus or concern is on a specific type or category of pet.
-
D.
hasCharacterContext
Indicates that a character is associated with or participates in a particular contextual situation, setting, or state.
-
E.
hasPerformanceContext
Indicates that an entity is associated with a specific performance-related situation, setting, or set of conditions under which it operates or is evaluated.
- 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_69d8dcf94c288190a06dea029ae4b223 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5a6b9be988190b5e3804c39dc7dd9 |
completed | April 20, 2026, 4:08 a.m. |
| PD | Predicate disambiguation | batch_69e48d1b10ec8190985c6fb5766ff981 |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:55 a.m.