Triple

T34482234
Position Surface form Disambiguated ID Type / Status
Subject IERS E885216 entity
Predicate hasComponent P35 FINISHED
Object IERS Earth Orientation Center
The IERS Earth Orientation Center is a scientific service that monitors and provides precise data on the Earth's rotation and orientation in space for global timekeeping and geodetic applications.
E254587 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: IERS Earth Orientation Center | Statement: [IERS, hasComponent, IERS Earth Orientation Center]
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: IERS Earth Orientation Center
Triple: [IERS, hasComponent, IERS Earth Orientation Center]
Generated description
The IERS Earth Orientation Center is a scientific service that monitors and provides precise data on the Earth's rotation and orientation in space for global timekeeping and geodetic applications.

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_69f349c947fc81909d30b53c194d6ea1 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f71ccf1fa88190801233dd72e88187 completed May 3, 2026, 10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3729d5abf88190bc72af8b0fb71590 completed June 21, 2026, 12:01 a.m.
NEDg Description generation batch_6a372a47f6a88190af8922a3af8c5eba completed June 21, 2026, 12:03 a.m.
NED2 Entity disambiguation (via description) batch_6a372acf6ce48190bec089a269da1194 completed June 21, 2026, 12:05 a.m.
Created at: May 1, 2026, 2:01 a.m.