Triple

T31805340
Position Surface form Disambiguated ID Type / Status
Subject Dolphin Reef (Eilat) E811855 entity
Predicate near P350 FINISHED
Object Eilat Coral Beach
Eilat Coral Beach is a popular marine nature reserve and snorkeling/diving site on the Red Sea in Eilat, Israel, known for its vibrant coral reefs and rich underwater life.
E1979112 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: Eilat Coral Beach | Statement: [Dolphin Reef (Eilat), near, Eilat Coral Beach]
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: Eilat Coral Beach
Triple: [Dolphin Reef (Eilat), near, Eilat Coral Beach]
Generated description
Eilat Coral Beach is a popular marine nature reserve and snorkeling/diving site on the Red Sea in Eilat, Israel, known for its vibrant coral reefs and rich underwater life.

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_69f348e70d188190b4637c5509f81274 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6acadf1fc8190ab46331eb4c35909 completed May 3, 2026, 2:02 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2e6598b548819096b458f43813fa9c completed June 14, 2026, 8:26 a.m.
NEDg Description generation batch_6a2e6658ee108190bbba5cd19e5aa157 completed June 14, 2026, 8:29 a.m.
NED2 Entity disambiguation (via description) batch_6a2e676fa6c88190bf81e145fa1cae24 completed June 14, 2026, 8:33 a.m.
Created at: April 30, 2026, 11:42 p.m.