Triple

T30650061

Position	Surface form	Disambiguated ID	Type / Status
Subject	Inhuman Resources	`E780229`	entity
Predicate	titleInFrench	`P6538`	FINISHED
Object	Dérapages Dérapages is the French title of the television series "Inhuman Resources," a dark drama about a disgraced former executive drawn into a sinister corporate role-play that spirals out of control.	`E1923226`	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: Dérapages | Statement: [Inhuman Resources, titleInFrench, Dérapages]

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: Dérapages
Triple: [Inhuman Resources, titleInFrench, Dérapages]

Generated description

Dérapages is the French title of the television series "Inhuman Resources," a dark drama about a disgraced former executive drawn into a sinister corporate role-play that spirals out of control.

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_69f224a5d2b481908a6853cd0138e2d7`	completed	April 29, 2026, 3:32 p.m.
NER	Named-entity recognition	`batch_69f68a975e1c81909d7424ae7af3410b`	completed	May 2, 2026, 11:36 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a2863fbbd388190a826a70f65793aae`	completed	June 9, 2026, 7:05 p.m.
NEDg	Description generation	`batch_6a2864de7ca081909869bd52d86a739a`	completed	June 9, 2026, 7:09 p.m.
NED2	Entity disambiguation (via description)	`batch_6a2865f827a48190848331baed146005`	completed	June 9, 2026, 7:14 p.m.

Created at: April 29, 2026, 8:30 p.m.