Triple
T10753146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Singapore–New York (ultra-long-haul) |
E253620
|
entity |
| Predicate | hasTypicalWestboundDurationHours |
P95793
|
FINISHED |
| Object | 18.5 |
—
|
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: 18.5 | Statement: [Singapore–New York (ultra-long-haul), hasTypicalWestboundDurationHours, 18.5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalWestboundDurationHours Context triple: [Singapore–New York (ultra-long-haul), hasTypicalWestboundDurationHours, 18.5]
-
A.
isFourHoursBehind
Indicates that one entity’s time zone or local time is exactly four hours earlier than another reference time or time zone.
-
B.
isThreeHoursBehind
Indicates that one entity’s time zone or local time is exactly three hours earlier than another entity’s.
-
C.
isTwoHoursBehind
Indicates that one entity’s time zone or clock is exactly two hours earlier than another entity’s time zone or clock.
-
D.
typicalDurationDays
Indicates the usual or expected number of days that an associated event, process, or state typically lasts.
-
E.
isInWesternPartOf
Indicates that one entity is located within the western part or region of another entity.
- 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_69d6aa5e51e8819095f06881cecf152e |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d71dc2543c8190bb060aa7a1fed6a6 |
completed | April 9, 2026, 3:32 a.m. |
| PD | Predicate disambiguation | batch_69d6f30df9948190ab3cdc33977fac14 |
completed | April 9, 2026, 12:30 a.m. |
| PDg | Predicate description generation | batch_69d6fa323564819097b207eb53f8a9b8 |
completed | April 9, 2026, 1 a.m. |
Created at: April 8, 2026, 9:15 p.m.