Triple
T19195139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Barrow |
E469945
|
entity |
| Predicate | rankInIrelandByLength |
P134821
|
FINISHED |
| Object | second-longest river in Ireland excluding tributaries |
—
|
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: second-longest river in Ireland excluding tributaries | Statement: [River Barrow, rankInIrelandByLength, second-longest river in Ireland excluding tributaries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankInIrelandByLength Context triple: [River Barrow, rankInIrelandByLength, second-longest river in Ireland excluding tributaries]
-
A.
rankByLengthInEurope
Indicates that entities are ordered or compared based on their length specifically within the context of Europe.
-
B.
leftIreland
Indicates that an entity departed from or moved away from Ireland.
-
C.
rankByLengthInWorld
Indicates ordering entities within a given world or context based on their length, from shortest to longest or vice versa.
-
D.
riverLength
Indicates the measured extent of a river from its source to its mouth, typically expressed as a linear distance.
-
E.
rankingByLengthInItaly
Indicates the relative ordering of entities based on their length within the context of Italy.
- 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_69d8dd0ad9088190a173b32657ae2e7a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f8a4d6b4819083fc5dd4dab05811 |
completed | April 20, 2026, 9:57 a.m. |
| PD | Predicate disambiguation | batch_69e4b9bb158481909478ca2e06f3ba39 |
completed | April 19, 2026, 11:17 a.m. |
| PDg | Predicate description generation | batch_69e4bfe9ef7081908a74a57d1fc731ea |
completed | April 19, 2026, 11:43 a.m. |
Created at: April 10, 2026, 12:07 p.m.