Triple
T35669499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bakırçay River valley |
E1030670
|
entity |
| Predicate | ancientNameOfRiver |
P183594
|
FINISHED |
| Object | Caicus |
—
|
NE NERFINISHED |
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: Caicus | Statement: [Bakırçay River valley, ancientNameOfRiver, Caicus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ancientNameOfRiver Context triple: [Bakırçay River valley, ancientNameOfRiver, Caicus]
-
A.
historicallyAssociatedRiver
Indicates a relationship where an entity has a notable historical connection or association with a particular river, such as through events, development, or cultural significance.
-
B.
associatedRiverBasin
Indicates that one entity is linked to, or lies within the drainage area of, a particular river basin.
-
C.
riverNameInGreek
Indicates that a river is known or referred to by a specific name in the Greek language.
-
D.
closelyAssociatedRiver
Indicates a river that is geographically or functionally closely connected to the subject, such as flowing nearby, through, or otherwise strongly linked to it.
-
E.
raceRiver
Indicates that an entity participates in a race that takes place on or along a river.
- 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_69f76e0acfc0819082c8495c2210ce73 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a01efcc08190bba489a9099b8684 |
completed | May 3, 2026, 7:21 p.m. |
| PD | Predicate disambiguation | batch_69f79e4d885881908a3612e2e75cf84f |
completed | May 3, 2026, 7:13 p.m. |
| PDg | Predicate description generation | batch_69f79f477c4c8190a35cb6d87b1dcbd1 |
completed | May 3, 2026, 7:17 p.m. |
Created at: May 3, 2026, 4:05 p.m.