Triple
T27727003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ko Haa |
E697326
|
entity |
| Predicate | approximateBoatTravelTimeFromKoLanta |
P165079
|
FINISHED |
| Object | about 1–1.5 hours |
—
|
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: about 1–1.5 hours | Statement: [Ko Haa, approximateBoatTravelTimeFromKoLanta, about 1–1.5 hours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateBoatTravelTimeFromKoLanta Context triple: [Ko Haa, approximateBoatTravelTimeFromKoLanta, about 1–1.5 hours]
-
A.
travelTimeByBoat
chosen
Indicates the amount of time it takes to travel between two locations specifically when using a boat as the mode of transportation.
-
B.
approximateBoatTravelTimeFromKarwar
Indicates the estimated duration it takes to travel by boat from Karwar to another specified location.
-
C.
timeToReachTown
Indicates the amount of time required for an entity to travel to and arrive at a specified town.
-
D.
approximateDrivingTimeFromLAnse
Indicates the estimated amount of time it takes to drive from L'Anse to another specified location.
-
E.
travelTimeByFerry
Indicates the duration required to travel between two locations specifically using a ferry as the mode of transportation.
- 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_69ef590c3e288190ad54d2465af8ca4e |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69fcc4b700748190ae00b21d09c96695 |
completed | May 7, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69fcb0f9d3d881908a049475182fb039 |
completed | May 7, 2026, 3:34 p.m. |
Created at: April 27, 2026, 3:09 p.m.