Triple
T9817796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Surface Laptop Go 3 |
E238451
|
entity |
| Predicate | hasFingerprintReader |
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: [Surface Laptop Go 3, hasFingerprintReader, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFingerprintReader Context triple: [Surface Laptop Go 3, hasFingerprintReader, yes]
-
A.
hasFingerprintSensor
chosen
Indicates that an entity is equipped with or includes a fingerprint recognition sensor.
-
B.
hasFaceUnlock
Indicates that an entity supports or is equipped with a facial recognition–based unlocking feature.
-
C.
hasNFC
Indicates that one entity possesses or supports Near Field Communication (NFC) capability in relation to another entity or context.
-
D.
includesBiometrics
Indicates that one entity contains, uses, or is associated with biometric data or biometric identifiers of another entity.
-
E.
hasPin
Indicates that one entity possesses, includes, or is equipped with a specific pin (such as a connector pin, security PIN, or fastening pin).
- 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_69ca84dfde1481909f47c286d715f892 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb2f5bfa481908a2d2cb3f3d7d585 |
completed | April 2, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69cd03e01ea881909a7d93fc3994ace5 |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:30 p.m.