Triple
T23496651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Angelo Fort |
E571721
|
entity |
| Predicate | distanceFromKannurTown |
P152612
|
FINISHED |
| Object | about 3 kilometers |
—
|
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 3 kilometers | Statement: [St. Angelo Fort, distanceFromKannurTown, about 3 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromKannurTown Context triple: [St. Angelo Fort, distanceFromKannurTown, about 3 kilometers]
-
A.
distanceFromMangaluru_km
Indicates the distance, measured in kilometers, between a given place and Mangaluru.
-
B.
distanceFromAngamaly_km
Indicates the distance, measured in kilometers, between a given place and Angamaly.
-
C.
distanceToKanyakumari
Indicates the spatial distance between a given location and Kanyakumari.
-
D.
distanceFromBengaluru
Indicates the measured spatial distance between a given entity’s location and the city of Bengaluru.
-
E.
distanceFromUdupi_km
Indicates the distance, measured in kilometers, between a given place and Udupi.
- 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_69e245b4829881909b77a70e942bbd54 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a7e00384819092729319a378d4ab |
completed | April 29, 2026, 6:40 a.m. |
| PD | Predicate disambiguation | batch_69f0621165c08190a0b27b1319733959 |
completed | April 28, 2026, 7:30 a.m. |
| PDg | Predicate description generation | batch_69f0bd4a0e408190ad8916faf23562d9 |
completed | April 28, 2026, 1:59 p.m. |
Created at: April 17, 2026, 6:05 p.m.