Triple
T23387557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unicode supplementary planes |
E593924
|
entity |
| Predicate | planeNumberRangeStart |
P152048
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Unicode supplementary planes, planeNumberRangeStart, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: planeNumberRangeStart Context triple: [Unicode supplementary planes, planeNumberRangeStart, 1]
-
A.
planeNumber
Indicates that an entity is associated with a specific airplane identification number (such as a tail number or flight number).
-
B.
firstPlaneRange
Indicates the distance or extent covered by the first plane in a comparative or multi-plane context.
-
C.
fleetNumbers
Indicates that there is an association between an entity and one or more identifying numbers assigned to it as part of a fleet.
-
D.
RVNumberRange
Indicates that a recreational vehicle’s number or identifier falls within a specified numeric range.
-
E.
aircraftCapacity
Indicates the maximum number of passengers or amount of load that an aircraft is designed or allowed to carry.
- 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_69e25d2754fc819085deea939bde60ab |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a498fd08819085e90a872d9d0c7a |
completed | April 29, 2026, 6:26 a.m. |
| PD | Predicate disambiguation | batch_69f061dde2e481908308952f9c0d3c2e |
completed | April 28, 2026, 7:29 a.m. |
| PDg | Predicate description generation | batch_69f07cbbd7488190ab3c8ae7d0fb68bf |
completed | April 28, 2026, 9:24 a.m. |
Created at: April 17, 2026, 5:35 p.m.