Triple

T7656283
Position Surface form Disambiguated ID Type / Status
Subject Tobu Skytree Line E173391 entity
Predicate terminus P388 FINISHED
Object Tobu-Dobutsu-Koen Station
Tobu-Dobutsu-Koen Station is a railway station in Miyashiro, Saitama Prefecture, Japan, serving as a key access point to the nearby Tobu Zoo and surrounding recreational area.
E2294413 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: Tobu-Dobutsu-Koen Station | Statement: [Tobu Skytree Line, terminus, Tobu-Dobutsu-Koen Station]
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: Tobu-Dobutsu-Koen Station
Triple: [Tobu Skytree Line, terminus, Tobu-Dobutsu-Koen Station]
Generated description
Tobu-Dobutsu-Koen Station is a railway station in Miyashiro, Saitama Prefecture, Japan, serving as a key access point to the nearby Tobu Zoo and surrounding recreational area.

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_69c69955517c819085bc715b96d304d2 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7018fcbb48190a479f2effd939a8e completed March 27, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7be310f1648190b20ce05296b9464b completed Aug. 12, 2026, 3:05 a.m.
NEDg Description generation batch_6a7be35f807c8190a23c1547eae23d51 completed Aug. 12, 2026, 3:07 a.m.
NED2 Entity disambiguation (via description) batch_6a7be3c660b48190bd5a2bb181daea94 completed Aug. 12, 2026, 3:08 a.m.
Created at: March 27, 2026, 3:59 p.m.