Triple

T24702464
Position Surface form Disambiguated ID Type / Status
Subject Middlesex County highway system E611788 entity
Predicate hasComponent P35 FINISHED
Object Middlesex County Route 501
Middlesex County Route 501 is a county highway in Middlesex County, New Jersey, that serves as part of the region’s local arterial road network.
E1647983 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: Middlesex County Route 501 | Statement: [Middlesex County highway system, hasComponent, Middlesex County Route 501]
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: Middlesex County Route 501
Triple: [Middlesex County highway system, hasComponent, Middlesex County Route 501]
Generated description
Middlesex County Route 501 is a county highway in Middlesex County, New Jersey, that serves as part of the region’s local arterial road network.

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_69e2c4d76d148190b58ad612467149a5 completed April 17, 2026, 11:40 p.m.
NER Named-entity recognition batch_69f40ff176408190b52be8c8b4b19e58 completed May 1, 2026, 2:29 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10100a18988190b906aab34df93072 completed May 22, 2026, 8:12 a.m.
NEDg Description generation batch_6a10136b70f4819096d05c3f3fed09c2 completed May 22, 2026, 8:27 a.m.
NED2 Entity disambiguation (via description) batch_6a10145483b88190898817902e5cb8c7 completed May 22, 2026, 8:31 a.m.
Created at: April 18, 2026, 3:23 a.m.