Triple

T27105624
Position Surface form Disambiguated ID Type / Status
Subject Pawtucket Falls E686568 entity
Predicate hasInfrastructure P2560 FINISHED
Object Pawtucket Dam
Pawtucket Dam is a historic hydroelectric and flood-control dam on the Merrimack River in Lowell, Massachusetts, central to the region’s early industrial development.
 E672779 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: Pawtucket Dam | Statement: [Pawtucket Falls, hasInfrastructure, Pawtucket Dam]
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: Pawtucket Dam
Triple: [Pawtucket Falls, hasInfrastructure, Pawtucket Dam]
Generated description
Pawtucket Dam is a historic hydroelectric and flood-control dam on the Merrimack River in Lowell, Massachusetts, central to the region’s early industrial development.

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_69ef148accd48190b6ed6e13a15f2a4f completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f623fcc6c881908e76b65c0ee51dd4 completed May 2, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12480a91a881909410b5f6a4aa1708 completed May 24, 2026, 12:36 a.m.
NEDg Description generation batch_6a124a032764819083399db3b9089018 completed May 24, 2026, 12:44 a.m.
NED2 Entity disambiguation (via description) batch_6a124a849c3c81908f1b3acdbaed65f8 completed May 24, 2026, 12:47 a.m.
Created at: April 27, 2026, 8:50 a.m.