Triple

T36399684
Position Surface form Disambiguated ID Type / Status
Subject Săcele E896587 entity
Predicate locatedOn P40 FINISHED
Object Timiș River
The Timiș River is a major watercourse in western Romania and northern Serbia that flows through the Banat region before joining the Danube.
E1047787 NE 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: Timiș River | Statement: [Săcele, locatedOn, Timiș River]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Timiș River
Triple: [Săcele, locatedOn, Timiș River]
Generated description
The Timiș River is a major watercourse in western Romania and northern Serbia that flows through the Banat region before joining the Danube.

Provenance (5 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_69f76e53b81081908d3b81860593f38a completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bd14f67c8190a87d049aba53a0a3 completed May 3, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39e6c908b08190ac34fafe8663ffe2 completed June 23, 2026, 1:52 a.m.
NEDg Description generation batch_6a39e82896d08190851ad8bb6a793b6a completed June 23, 2026, 1:58 a.m.
NED2 Entity disambiguation (via description) batch_6a39e88d8954819083d2669a9223a0aa completed June 23, 2026, 1:59 a.m.
Created at: May 3, 2026, 4:10 p.m.