Triple

T29009244
Position Surface form Disambiguated ID Type / Status
Subject Armed Forces of Azerbaijan E736517 entity
Predicate hasBranch P35 FINISHED
Object Azerbaijani Land Forces
The Azerbaijani Land Forces are the primary ground warfare branch of Azerbaijan’s military, responsible for land-based defense and combat operations.
 E736517 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: Azerbaijani Land Forces | Statement: [Armed Forces of Azerbaijan, hasBranch, Azerbaijani Land Forces]
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: Azerbaijani Land Forces
Triple: [Armed Forces of Azerbaijan, hasBranch, Azerbaijani Land Forces]
Generated description
The Azerbaijani Land Forces are the primary ground warfare branch of Azerbaijan’s military, responsible for land-based defense and combat operations.

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_69f077eb81e88190ad9ff62cbb9f555e completed April 28, 2026, 9:03 a.m.
NER Named-entity recognition batch_69f65fda92188190b20bfd59902ed27d completed May 2, 2026, 8:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25504352cc8190acd86066194a818d completed June 7, 2026, 11:04 a.m.
NEDg Description generation batch_6a25557bdab48190b158a06a1f9c3b3c completed June 7, 2026, 11:26 a.m.
NED2 Entity disambiguation (via description) batch_6a2555d685d48190b093fc8a960d8bcb completed June 7, 2026, 11:28 a.m.
Created at: April 28, 2026, 9:40 a.m.