Triple

T29767481
Position Surface form Disambiguated ID Type / Status
Subject Fort Sherman E753953 entity
Predicate hasFacility P105 FINISHED
Object jungle warfare training center
A jungle warfare training center is a specialized military facility where troops are prepared for combat and survival operations in dense, tropical environments.
E1885334 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: jungle warfare training center | Statement: [Fort Sherman, hasFacility, jungle warfare training 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: jungle warfare training center
Triple: [Fort Sherman, hasFacility, jungle warfare training center]
Generated description
A jungle warfare training center is a specialized military facility where troops are prepared for combat and survival operations in dense, tropical environments.

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_69f0ef827ff88190ade56e0b0846b713 completed April 28, 2026, 5:33 p.m.
NER Named-entity recognition batch_69f6745d64ec8190a4726ed224b82873 completed May 2, 2026, 10:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26c8f268f88190bd8f9fe56cc1cf81 completed June 8, 2026, 1:51 p.m.
NEDg Description generation batch_6a26ccffc0988190be22b829efed1b24 completed June 8, 2026, 2:09 p.m.
NED2 Entity disambiguation (via description) batch_6a26da49ea808190bba6584022192015 completed June 8, 2026, 3:05 p.m.
Created at: April 28, 2026, 8:39 p.m.