Triple

T38208964
Position Surface form Disambiguated ID Type / Status
Subject Oakwood Cemetery (Fort Worth, Texas) E1009284 entity
Predicate hasCoordinateRegion P285 FINISHED
Object Northern Fort Worth
Northern Fort Worth is a geographic area in the northern part of Fort Worth, Texas, encompassing neighborhoods, commercial districts, and landmarks such as Oakwood Cemetery.
E2261179 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: Northern Fort Worth | Statement: [Oakwood Cemetery (Fort Worth, Texas), hasCoordinateRegion, Northern Fort Worth]
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: Northern Fort Worth
Triple: [Oakwood Cemetery (Fort Worth, Texas), hasCoordinateRegion, Northern Fort Worth]
Generated description
Northern Fort Worth is a geographic area in the northern part of Fort Worth, Texas, encompassing neighborhoods, commercial districts, and landmarks such as Oakwood Cemetery.

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_69f76dc94fcc8190bd2f55e81f9d6527 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69fcb13354508190bd9cd1509b7c8b6f completed May 7, 2026, 3:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a418545089c81909ffcbc61a600aed0 completed June 28, 2026, 8:34 p.m.
NEDg Description generation batch_6a41863dcc6c81908e217dc88ed198e3 completed June 28, 2026, 8:38 p.m.
NED2 Entity disambiguation (via description) batch_6a4186bd16b88190bcc521382c3e7fb7 completed June 28, 2026, 8:40 p.m.
Created at: May 3, 2026, 4:30 p.m.