Triple
T15126462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hari River |
E361301
|
entity |
| Predicate | borderSectionLengthApproxKm |
P69395
|
FINISHED |
| Object | 100 |
—
|
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: 100 | Statement: [Hari River, borderSectionLengthApproxKm, 100]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderSectionLengthApproxKm Context triple: [Hari River, borderSectionLengthApproxKm, 100]
-
A.
borderSectionLength
chosen
Indicates the measured length of a specific segment of a shared border between two geographic or administrative areas.
-
B.
lengthInKm
Indicates that one entity specifies the length or distance of another entity measured in kilometers.
-
C.
trackLengthApproxKm
Indicates that one entity has an approximate track length, measured in kilometers, associated with it.
-
D.
shareBorderLengthApprox
Indicates that two entities share a common boundary whose length is approximately equal to a specified value.
-
E.
borderSectionOf
Indicates that one entity represents a specific segment or portion of the overall border of another entity.
- 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_69d85a06450081909c5a14ea9851a15e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005a1b9288190954f2d92549805e5 |
completed | April 15, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69deb96c1d9c81909351558ed97bc5b7 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:06 a.m.