Triple

T30808471
Position Surface form Disambiguated ID Type / Status
Subject Loddon River E784571 entity
Predicate hasTributary P415 FINISHED
Object Serpentine Creek
Serpentine Creek is a minor watercourse in Victoria, Australia, that serves as a tributary within the Loddon River catchment.
E2294407 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: Serpentine Creek | Statement: [Loddon River, hasTributary, Serpentine Creek]
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: Serpentine Creek
Triple: [Loddon River, hasTributary, Serpentine Creek]
Generated description
Serpentine Creek is a minor watercourse in Victoria, Australia, that serves as a tributary within the Loddon River catchment.

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_69f224b3a7ec819096939414d103e31e completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f6904138088190ad4209ce7caa4ea3 completed May 3, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a7be310f1648190b20ce05296b9464b completed Aug. 12, 2026, 3:05 a.m.
NEDg Description generation batch_6a7be35f807c8190a23c1547eae23d51 completed Aug. 12, 2026, 3:07 a.m.
NED2 Entity disambiguation (via description) batch_6a7be3c660b48190bd5a2bb181daea94 completed Aug. 12, 2026, 3:08 a.m.
Created at: April 29, 2026, 8:43 p.m.