Triple
T8520987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Motorola Droid |
E201691
|
entity |
| Predicate | widthMillimeters |
P619
|
FINISHED |
| Object | 60 |
—
|
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: 60 | Statement: [Motorola Droid, widthMillimeters, 60]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: widthMillimeters Context triple: [Motorola Droid, widthMillimeters, 60]
-
A.
width
chosen
Indicates the measurement of how wide an entity is, typically the extent of its horizontal dimension from side to side.
-
B.
dimensionOfLength
Indicates that something represents or specifies a measurement along a single spatial extent (a length dimension).
-
C.
depthMetresApprox
Indicates an approximate measurement of how deep something is in metres, rather than an exact value.
-
D.
typicalWidth
Indicates the usual or characteristic width associated with an entity, as opposed to an exact or measured width in a specific instance.
-
E.
properLengthMeasuredIn
Indicates that the proper (intrinsic or rest-frame) length of an entity is expressed using a specified unit of measurement.
- 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_69ca8321bb44819081b74df0b710276d |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe62a490481908ee0ad4ba9a94682 |
completed | March 31, 2026, 3:20 p.m. |
| PD | Predicate disambiguation | batch_69cbd10f64b4819080859057c19e58f0 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:16 p.m.