Triple
T6094308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TI-86 |
E135838
|
entity |
| Predicate | hasPhysicalInterface |
P68076
|
FINISHED |
| Object | keypad |
—
|
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: keypad | Statement: [TI-86, hasPhysicalInterface, keypad]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhysicalInterface Context triple: [TI-86, hasPhysicalInterface, keypad]
-
A.
hasCommunicationInterface
Indicates that one entity provides or supports a specific means or channel through which it can communicate or exchange data with another entity or system.
-
B.
hasPhysicalFootprint
Indicates that one entity occupies or affects a specific physical area or space in the real world.
-
C.
usesPhysicalLayerPipe
Indicates that one entity employs a specific physical-layer transmission path or channel provided by another entity to carry its data.
-
D.
usesPhysicalLayerSimilarTo
Indicates that one entity employs a physical layer that is similar in structure, technology, or operational characteristics to that used by another entity.
-
E.
hasPhysicalNature
Indicates that one entity possesses or exhibits a specific physical form, composition, or material nature in relation to another.
- 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_69c0087cd3c48190b459848c72d84eb1 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05a9516ec819093e94ee8d3244e1b |
completed | March 22, 2026, 9:09 p.m. |
| PD | Predicate disambiguation | batch_69c049f3b1ec8190bea67a7bec6442a5 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04e8e3f2c8190be459ca02f9b315a |
completed | March 22, 2026, 8:18 p.m. |
Created at: March 22, 2026, 4:12 p.m.