Triple

T27371859
Position Surface form Disambiguated ID Type / Status
Subject Aquilla, Texas E690345 entity
Predicate locatedNear P294 FINISHED
Object Aquilla Lake
Aquilla Lake is a reservoir in central Texas used primarily for flood control, water supply, and outdoor recreation such as fishing and boating.
 E2297560 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: Aquilla Lake | Statement: [Aquilla, Texas, locatedNear, Aquilla Lake]
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: Aquilla Lake
Triple: [Aquilla, Texas, locatedNear, Aquilla Lake]
Generated description
Aquilla Lake is a reservoir in central Texas used primarily for flood control, water supply, and outdoor recreation such as fishing and boating.

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_69ef51ff826081909e42c8e2bfb97941 completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62c62e6c88190924d41dabdaabd1e completed May 2, 2026, 4:54 p.m.
NED1 Entity disambiguation (via context triple) batch_6a83a627ec88819094a5028a821a741b completed Aug. 18, 2026, 12:24 a.m.
NEDg Description generation batch_6a83a67723ac8190b04b6b846f9bee8f completed Aug. 18, 2026, 12:25 a.m.
NED2 Entity disambiguation (via description) batch_6a83a705a05c8190a1505ffade5ec704 completed Aug. 18, 2026, 12:27 a.m.
Created at: April 27, 2026, 12:19 p.m.