Triple

T38186010
Position Surface form Disambiguated ID Type / Status
Subject Half-Life 2: Episode Two E1005316 entity
Predicate setting P1957 FINISHED
Object White Forest
White Forest is a Resistance stronghold and missile base hidden in the forests of Eastern Europe in Half-Life 2: Episode Two, serving as a key strategic location in the fight against the Combine.
E2259183 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: White Forest | Statement: [Half-Life 2: Episode Two, setting, White Forest]
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: White Forest
Triple: [Half-Life 2: Episode Two, setting, White Forest]
Generated description
White Forest is a Resistance stronghold and missile base hidden in the forests of Eastern Europe in Half-Life 2: Episode Two, serving as a key strategic location in the fight against the Combine.

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_69f76dbc22c481908139b694ffde7a0c completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69fcb112bcb08190aae375846845fd66 completed May 7, 2026, 3:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a417b3bd7ec81909dcc5073a32200e9 completed June 28, 2026, 7:51 p.m.
NEDg Description generation batch_6a417d1656708190bfbb844ce3724726 completed June 28, 2026, 7:59 p.m.
NED2 Entity disambiguation (via description) batch_6a417daed5e08190bb5482e6a4a70c98 completed June 28, 2026, 8:01 p.m.
Created at: May 3, 2026, 4:29 p.m.