Triple

T277396
Position Surface form Disambiguated ID Type / Status
Subject SAS E5277 entity
Predicate usedInIndustry P8461 FINISHED
Object pharmaceutical industry LITERAL 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: pharmaceutical industry | Statement: [SAS, usedInIndustry, pharmaceutical industry]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usedInIndustry
Context triple: [SAS, usedInIndustry, pharmaceutical industry]
  • A. alsoUsedIn
    Indicates that something is additionally employed, applied, or present in another context, setting, or use case beyond the primary one.
  • B. usedInProductLine
    Indicates that something (such as a component, material, or feature) is utilized within a particular product line.
  • C. usedOn
    Indicates that one entity is applied to, operated on, or otherwise utilized in relation to another entity.
  • D. usedFor
    Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
  • E. usedInCountry
    Indicates that something is utilized, applied, or in operation within the specified country.
  • F. None of above. chosen

Provenance (4 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_69a257e6c8788190987dfe705ca2912a completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25ded68c88190b1fc595ce329aeb9 completed Feb. 28, 2026, 3:15 a.m.
PD Predicate disambiguation batch_69a25b7480e881909399beccfc7ffb81 completed Feb. 28, 2026, 3:05 a.m.
PDg Predicate description generation batch_69a25c2d94388190aeda17ddd42b4ac9 completed Feb. 28, 2026, 3:08 a.m.
Created at: Feb. 28, 2026, 2:59 a.m.