Triple
T13749872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Do U |
E330315
|
entity |
| Predicate | hasBobbyDigitalPersona |
P61233
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Do U, hasBobbyDigitalPersona, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBobbyDigitalPersona Context triple: [Do U, hasBobbyDigitalPersona, true]
-
A.
hasFingerprintSensor
Indicates that an entity is equipped with or includes a fingerprint recognition sensor.
-
B.
hasProcessOfRecognition
Indicates that one entity is involved in or characterized by a process of recognizing, identifying, or acknowledging another entity or condition.
-
C.
hasPersona
chosen
Indicates that an entity possesses or is associated with a particular persona, role, or character profile.
-
D.
hasFaceUnlock
Indicates that an entity supports or is equipped with a facial recognition–based unlocking feature.
-
E.
includesBiometrics
Indicates that one entity contains, uses, or is associated with biometric data or biometric identifiers of another entity.
- 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_69d81c573f288190aa2403d484fa3d49 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02148c208190a882927905a861a6 |
completed | April 14, 2026, 9 a.m. |
| PD | Predicate disambiguation | batch_69dbbe950b148190ba0df8a749269ec6 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 10:08 p.m.