Triple
T641424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pixel 7 |
E16746
|
entity |
| Predicate | hasFingerprintSensor |
P17643
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Pixel 7, hasFingerprintSensor, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFingerprintSensor Context triple: [Pixel 7, hasFingerprintSensor, yes]
-
A.
hasPin
Indicates that one entity possesses, includes, or is equipped with a specific pin (such as a connector pin, security PIN, or fastening pin).
-
B.
hasFormFactor
Indicates that one entity possesses or is characterized by a particular physical or structural form factor defined by another entity.
-
C.
hasUSBPort
Indicates that one entity is equipped with or includes a USB port available for connection or data/power transfer.
-
D.
hasKeypadLayout
Indicates that one entity possesses or uses a specific arrangement or configuration of keys or buttons provided by another entity.
-
E.
hasBackupBattery
Indicates that an entity is equipped with an additional battery intended to provide power when the primary power source is unavailable or fails.
- 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_69a4936be1c88190af56540324b57da7 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49f02bc2c8190b8a92b2505768c19 |
completed | March 1, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69a49d0830008190a26ee158ed4dd1fe |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49df0de3c81909721eb391ec94031 |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:36 p.m.