Triple
T38030646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taj Exotica Resort & Spa, Maldives |
E948897
|
entity |
| Predicate | distanceFromMaléInternationalAirport |
P201704
|
FINISHED |
| Object | approximately 15 minutes by speedboat |
—
|
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: approximately 15 minutes by speedboat | Statement: [Taj Exotica Resort & Spa, Maldives, distanceFromMaléInternationalAirport, approximately 15 minutes by speedboat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromMaléInternationalAirport Context triple: [Taj Exotica Resort & Spa, Maldives, distanceFromMaléInternationalAirport, approximately 15 minutes by speedboat]
-
A.
distanceToMalé
chosen
Indicates the measured spatial distance between a given location or object and Malé.
-
B.
distanceToKLIA
Indicates the measured distance between a given location and Kuala Lumpur International Airport (KLIA).
-
C.
distanceFromNgurahRaiAirport
Indicates the measured distance between a given location and Ngurah Rai Airport.
-
D.
distanceToAlorSetar_km
Indicates the distance, measured in kilometers, from a given location to Alor Setar.
-
E.
distanceFromDenpasar
Indicates the spatial distance between a given location and Denpasar.
- 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_69f76efd1bc48190a729097fe5177b61 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037df1223c8190a5d61e4f8e6fd613 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a037a1ad6c48190bfe35d350c1b4751 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:20 p.m.