Triple

T34840845
Position Surface form Disambiguated ID Type / Status
Subject Abita Springs, Louisiana E1004335 entity
Predicate namedAfter P63 FINISHED
Object Abita Creek
Abita Creek is a small waterway in southeastern Louisiana known for its clear, spring-fed waters that gave rise to the nearby town of Abita Springs and its historic reputation for pure drinking water.
E2297679 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: Abita Creek | Statement: [Abita Springs, Louisiana, namedAfter, Abita 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: Abita Creek
Triple: [Abita Springs, Louisiana, namedAfter, Abita Creek]
Generated description
Abita Creek is a small waterway in southeastern Louisiana known for its clear, spring-fed waters that gave rise to the nearby town of Abita Springs and its historic reputation for pure drinking water.

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_69f76db97714819099b5bed36fd64e9d completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7812ef82c819085c6119c2272fb7d completed May 3, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a83c0bb2a148190b3e9b7f570a5da3a completed Aug. 18, 2026, 2:17 a.m.
NEDg Description generation batch_6a83c19a154081908303097c65b08b27 completed Aug. 18, 2026, 2:21 a.m.
NED2 Entity disambiguation (via description) batch_6a83c1f1ba3c81908a8bf5fb6fc78598 completed Aug. 18, 2026, 2:22 a.m.
Created at: May 3, 2026, 4 p.m.