Triple

T26434656
Position Surface form Disambiguated ID Type / Status
Subject Cahaba, Alabama E664605 entity
Predicate hasHistoricStructure P1098 FINISHED
Object Cemetery of Cahaba
The Cemetery of Cahaba is a historic burial ground associated with the former state capital and ghost town of Cahaba, Alabama, containing graves that reflect the area's 19th-century history.
E1724346 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: Cemetery of Cahaba | Statement: [Cahaba, Alabama, hasHistoricStructure, Cemetery of Cahaba]
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: Cemetery of Cahaba
Triple: [Cahaba, Alabama, hasHistoricStructure, Cemetery of Cahaba]
Generated description
The Cemetery of Cahaba is a historic burial ground associated with the former state capital and ghost town of Cahaba, Alabama, containing graves that reflect the area's 19th-century history.

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_69ee883ad6a4819088f918e76122d690 completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f61210575c8190b84b012054b6f26d completed May 2, 2026, 3:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11aecbfdec8190902b1a85c27f3266 completed May 23, 2026, 1:42 p.m.
NEDg Description generation batch_6a11af9c1be081909d2e461e3da596d6 completed May 23, 2026, 1:46 p.m.
NED2 Entity disambiguation (via description) batch_6a11b051d328819090f947755dda4cfc completed May 23, 2026, 1:49 p.m.
Created at: April 26, 2026, 11:52 p.m.