Triple

T38136802
Position Surface form Disambiguated ID Type / Status
Subject Fort Point (naming convention) E952371 entity
Predicate hasExample P1259 FINISHED
Object Fort Point, New Hampshire
Fort Point, New Hampshire is a coastal area in New Castle known for its historic military fortifications and scenic views at the mouth of the Piscataqua River.
E2258070 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: Fort Point, New Hampshire | Statement: [Fort Point (naming convention), hasExample, Fort Point, New Hampshire]
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: Fort Point, New Hampshire
Triple: [Fort Point (naming convention), hasExample, Fort Point, New Hampshire]
Generated description
Fort Point, New Hampshire is a coastal area in New Castle known for its historic military fortifications and scenic views at the mouth of the Piscataqua River.

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_69f76f09a7148190a4b91c0bacdc127a completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fc4606af388190864b27fa60c202c1 completed May 7, 2026, 7:57 a.m.
NED1 Entity disambiguation (via context triple) batch_6a417126c5f48190b4bb8f4cd2cbdb84 completed June 28, 2026, 7:08 p.m.
NEDg Description generation batch_6a4173143a308190828a5cb1be6e4f2d completed June 28, 2026, 7:16 p.m.
NED2 Entity disambiguation (via description) batch_6a41738d9b508190ad95d1f67ce42904 completed June 28, 2026, 7:18 p.m.
Created at: May 3, 2026, 4:21 p.m.