Triple
T21849654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanjung Lesung |
E539469
|
entity |
| Predicate | travelTimeFromJakartaByCar |
P145559
|
FINISHED |
| Object | approximately 3 to 4 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: approximately 3 to 4 hours | Statement: [Tanjung Lesung, travelTimeFromJakartaByCar, approximately 3 to 4 hours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelTimeFromJakartaByCar Context triple: [Tanjung Lesung, travelTimeFromJakartaByCar, approximately 3 to 4 hours]
-
A.
distanceToJakarta_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and Jakarta.
-
B.
travelTimeFromKotaKinabalu
Indicates the amount of time required to travel from Kota Kinabalu to another specified location or entity.
-
C.
distanceToMataram
Indicates the measured spatial distance between a given entity’s location and the location of Mataram.
-
D.
distanceToBandung
Indicates the spatial distance between a given location or entity and the city of Bandung.
-
E.
distanceToKota
Indicates the measured distance between a given entity and the location referred to as Kota.
- 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_69e0c476c3c88190a92d08ebb59a128a |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f0bd582ca48190890648fdee2a0c6e |
completed | April 28, 2026, 1:59 p.m. |
| PD | Predicate disambiguation | batch_69e6be8c14748190bdcc44a14d50bea4 |
completed | April 21, 2026, 12:02 a.m. |
| PDg | Predicate description generation | batch_69e6c187bc548190b4ca13150f6bae38 |
completed | April 21, 2026, 12:15 a.m. |
Created at: April 16, 2026, 6:55 p.m.