Triple
T5315850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brazos River |
E119144
|
entity |
| Predicate | stateRankByLength |
P18229
|
FINISHED |
| Object | one of the longest rivers in Texas |
—
|
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: one of the longest rivers in Texas | Statement: [Brazos River, stateRankByLength, one of the longest rivers in Texas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stateRankByLength Context triple: [Brazos River, stateRankByLength, one of the longest rivers in Texas]
-
A.
stateRank
Indicates the relative position or standing of an entity within a specific state-level ordering or hierarchy.
-
B.
rankByLengthInNorthAmerica
Indicates that entities are ordered or compared based on their length, considering only those located in or relevant to North America.
-
C.
rankByLengthInWorld
Indicates ordering entities within a given world or context based on their length, from shortest to longest or vice versa.
-
D.
areaRankInUS
Indicates the relative position of an entity in a ranking of areas within the United States, based on its size.
-
E.
rankByLength
chosen
Indicates ordering a set of items based on their length, typically from shortest to longest or vice versa.
- 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_69bd446b57bc8190a513d2e6c40314f3 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd86f20f008190be7b5848af05f2b8 |
completed | March 20, 2026, 5:42 p.m. |
| PD | Predicate disambiguation | batch_69bd84534f9c8190bc19d4812060768d |
completed | March 20, 2026, 5:30 p.m. |
Created at: March 20, 2026, 1:54 p.m.